score-optimize actuator/storage/platform allocation, enforce structural feasibility

The saved composite score previously came from a requirement-solve that
only satisfied the platform's physical performance floor, not the
domain's actual weighted score -- a smaller/cheaper build could always
score higher by hand. _decide_masses now jointly searches platform,
actuator, and storage mass (coarse-to-fine grid, no external deps) to
maximize the domain's real weighted composite score, with the
requirement floor as a lower bound rather than the final answer.

Platform mass specifically was previously fixed at a geometric-mean
representative value, which could be too little structure to carry its
own required actuator+storage (reusing CARGO_KG_PER_STRUCTURAL_KG, the
existing structure-carries-N-times-its-mass ratio, applied to a
platform carrying its own powertrain instead of cargo). Growing
platform mass also raises that structural ceiling, so it has to be
searched jointly rather than fixed or bounded independently.

Because power_density/range_fuel/cost_efficiency are all per-kg
ratios, none of them naturally penalize a build whose absolute mass
exceeds its own platform's declared ceiling -- a Piston Engine sized
for a Hyperloop could still score well on a Light Personal Vehicle.
Pass 2 now detects genuine infeasibility (no platform mass within its
own declared ceiling can structurally carry the required floor) and
saves it as a per-domain block instead of a misleadingly good score.

Also adds an explore-panel warning (not a hard block, since exploration
is intentionally loose) when a manually-dragged slider build exceeds
the platform's mass ceiling or structural carrying capacity.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

src/physcom/db/repository.py

@@ -230,24 +230,37 @@ class Repository:
         self.conn.commit()
         return row["id"]
 
-    def backfill_lower_is_better(self, domain_name: str, metric_name: str) -> None:
-        """Set lower_is_better=1 for an existing domain-metric row that still has the default 0."""
+    def sync_domain_metric_weights(self, domain: Domain) -> None:
+        """Make domain_metric_weights exactly match domain.metric_bounds on an
+        already-seeded domain: upserts weight/norm_min/norm_max/unit for every
+        currently-declared metric, and deletes any row for a metric that's been
+        removed from the domain (e.g. safety/availability dropped from the
+        scored set). Safe to call whether the domain was just freshly inserted
+        or already existed.
+        """
+        row = self.conn.execute(
+            "SELECT id FROM domains WHERE name = ?", (domain.name,)
+        ).fetchone()
+        if not row:
+            return
+        domain_id = row["id"]
+        keep_ids = []
+        for mb in domain.metric_bounds:
+            metric_id = self.ensure_metric(mb.metric_name, unit=mb.unit)
+            keep_ids.append(metric_id)
             self.conn.execute(
-            """UPDATE domain_metric_weights SET lower_is_better = 1
-               WHERE lower_is_better = 0
-                 AND domain_id = (SELECT id FROM domains WHERE name = ?)
-                 AND metric_id = (SELECT id FROM metrics WHERE name = ?)""",
-            (domain_name, metric_name),
+                """INSERT OR REPLACE INTO domain_metric_weights
+                   (domain_id, metric_id, weight, norm_min, norm_max, lower_is_better, unit)
+                   VALUES (?, ?, ?, ?, ?, ?, ?)""",
+                (domain_id, metric_id, mb.weight, mb.norm_min, mb.norm_max,
+                 int(mb.lower_is_better), mb.unit),
             )
-        self.conn.commit()
-
-    def backfill_metric_unit(self, domain_name: str, metric_name: str, unit: str) -> None:
-        """Set this domain-metric row's unit — unit is domain-scoped, not global to the metric name."""
+        if keep_ids:
+            placeholders = ",".join("?" * len(keep_ids))
             self.conn.execute(
-            """UPDATE domain_metric_weights SET unit = ?
-               WHERE domain_id = (SELECT id FROM domains WHERE name = ?)
-                 AND metric_id = (SELECT id FROM metrics WHERE name = ?)""",
-            (unit, domain_name, metric_name),
+                f"""DELETE FROM domain_metric_weights
+                    WHERE domain_id = ? AND metric_id NOT IN ({placeholders})""",
+                (domain_id, *keep_ids),
             )
         self.conn.commit()
 
@@ -593,15 +606,18 @@ class Repository:
         llm_review: str | None = None,
         human_notes: str | None = None,
         domain_block_reason: str | None = None,
+        qualitative_rating: str | None = None,
         commit: bool = True,
     ) -> None:
         self.conn.execute(
             """INSERT OR REPLACE INTO combination_results
                (combination_id, domain_id, composite_score, novelty_flag,
-                llm_review, human_notes, pass_reached, domain_block_reason)
-               VALUES (?, ?, ?, ?, ?, ?, ?, ?)""",
+                llm_review, human_notes, pass_reached, domain_block_reason,
+                qualitative_rating)
+               VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)""",
             (combo_id, domain_id, composite_score, novelty_flag,
-             llm_review, human_notes, pass_reached, domain_block_reason),
+             llm_review, human_notes, pass_reached, domain_block_reason,
+             qualitative_rating),
         )
         if commit:
             self.conn.commit()
@@ -641,6 +657,20 @@ class Repository:
             ).fetchall()
         return {r["status"]: r["cnt"] for r in rows}
 
+    def count_results_by_rating(self, domain_name: str) -> dict[str, int]:
+        """Count results by qualitative_rating (LOW/MEDIUM/HIGH) for a domain.
+        Rows with no rating (not yet pass-4 reviewed, or reviewed before this
+        existed) are excluded, not bucketed as a pseudo-status."""
+        rows = self.conn.execute(
+            """SELECT cr.qualitative_rating as rating, COUNT(*) as cnt
+               FROM combination_results cr
+               JOIN domains d ON cr.domain_id = d.id
+               WHERE d.name = ? AND cr.qualitative_rating IS NOT NULL
+               GROUP BY cr.qualitative_rating""",
+            (domain_name,),
+        ).fetchall()
+        return {r["rating"]: r["cnt"] for r in rows}
+
     def get_pipeline_summary(self, domain_name: str) -> dict | None:
         """Return a summary of results for a domain, or None if no results."""
         row = self.conn.execute(
@@ -685,8 +715,12 @@ class Repository:
         ).fetchone()
         return dict(row) if row else None
 
-    def get_all_results(self, domain_name: str, status: str | None = None) -> list[dict]:
-        """Return all results for a domain, optionally filtered by combo status."""
+    def get_all_results(
+        self, domain_name: str, status: str | None = None, rating: str | None = None
+    ) -> list[dict]:
+        """Return all results for a domain, optionally filtered by combo
+        status and/or qualitative_rating (LOW/MEDIUM/HIGH, independent filters
+        that combine with AND)."""
         query = """SELECT cr.*, c.hash, c.status as combo_status, d.name as domain_name
                    FROM combination_results cr
                    JOIN combinations c ON cr.combination_id = c.id
@@ -698,6 +732,9 @@ class Repository:
         elif status:
             query += " AND c.status = ? AND cr.domain_block_reason IS NULL"
             params.append(status)
+        if rating:
+            query += " AND cr.qualitative_rating = ?"
+            params.append(rating)
         query += " ORDER BY cr.composite_score DESC"
         rows = self.conn.execute(query, params).fetchall()
         combo_ids = [r["combination_id"] for r in rows]
@@ -712,6 +749,7 @@ class Repository:
                 "pass_reached": r["pass_reached"],
                 "domain_id": r["domain_id"],
                 "domain_block_reason": r["domain_block_reason"],
+                "qualitative_rating": r["qualitative_rating"],
             }
             for r in rows
         ]

src/physcom/db/schema.py

@@ -91,6 +91,7 @@ CREATE TABLE IF NOT EXISTS combination_results (
     human_notes         TEXT,
     pass_reached        INTEGER,
     domain_block_reason TEXT,
+    qualitative_rating  TEXT,
     UNIQUE(combination_id, domain_id)
 );
 
@@ -165,6 +166,10 @@ def _migrate(conn: sqlite3.Connection) -> None:
         conn.execute(
             "ALTER TABLE combination_results ADD COLUMN domain_block_reason TEXT"
         )
+    if "qualitative_rating" not in result_cols:
+        conn.execute(
+            "ALTER TABLE combination_results ADD COLUMN qualitative_rating TEXT"
+        )
 
     # Backfill: cost_efficiency is lower-is-better in all domains
     conn.execute(

src/physcom/llm/base.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 from abc import ABC, abstractmethod
 
-from physcom.models.domain import MetricBound
+from physcom.models.domain import Domain, MetricBound
 
 
 class LLMRateLimitError(Exception):
@@ -40,7 +40,7 @@ class LLMProvider(ABC):
         combination_description: str,
         raw_metrics: dict[str, float],
         normalized_scores: dict[str, float],
-        metrics: list[MetricBound],
+        domain: Domain,
     ) -> tuple[str, bool]:
         """Given a combination, its raw physical estimates, and their
         normalized scores, return a (text, is_plausible) tuple:
@@ -50,6 +50,11 @@ class LLMProvider(ABC):
         normalized score) so the review can reason from the actual physics
         rather than only a compressed 0-1 number, which can look
         deceptively bad for a metric whose scale was built for a different
-        kind of vehicle. `metrics` carries each metric's unit for
-        formatting the raw value meaningfully."""
+        kind of vehicle. `domain` carries both each metric's unit (via
+        domain.metric_bounds, for formatting the raw value meaningfully)
+        and the domain's own name/description, so the review judges a
+        metric like range against what THIS domain actually needs rather
+        than generic real-world expectations for the platform category
+        (e.g. a short-hop domain shouldn't get judged against typical
+        long-haul aircraft range)."""
         ...

src/physcom/llm/parsing.py

@@ -16,6 +16,13 @@ def parse_verdict(text: str) -> bool:
     return True
 
 
+def parse_rating(text: str) -> str | None:
+    """Extract RATING: LOW/MEDIUM/HIGH from response; None if absent (older
+    reviews saved before this existed, or a malformed response)."""
+    m = re.search(r"RATING:\s*(LOW|MEDIUM|HIGH)", text, re.IGNORECASE)
+    return m.group(1).upper() if m else None
+
+
 def parse_metric_json(text: str, metrics: list[MetricBound]) -> dict[str, float]:
     """Strip markdown fences and parse JSON; fall back to each metric's own
     norm_min/norm_max midpoint on error — a flat constant like 0.5 is

src/physcom/llm/prompts.py

@@ -116,6 +116,14 @@ You are reviewing a transportation concept for real-world viability — could th
 actually be built and operated safely. Whether it is new, exciting, or original
 is NOT the question.
 
+## Domain
+This concept is being evaluated for "{domain_name}": {domain_description}
+Judge every metric against what THIS domain actually needs, not general
+expectations for the platform category. A range far beyond what this domain
+requires is a strength or a non-issue, never a weakness -- don't reason about
+range, speed, or capacity by comparing to what other vehicles of this type
+typically have in general use; compare to what this specific domain calls for.
+
 ## Concept
 {description}
 
@@ -139,6 +147,14 @@ before treating the score as evidence of a problem.
 
 {scores}
 
+Safety and accessibility (infrastructure/regulatory availability) are NOT
+among the scores above — neither reduces to a physics formula the way the
+metrics above do, so nothing here estimates them numerically. Reason about
+both directly from the concept description: does this combination carry a
+specific safety hazard, and is the infrastructure/regulatory environment it
+needs realistic? Both feed into the RATING below as qualitative judgment
+calls, not as scores of their own.
+
 ## What makes something IMPLAUSIBLE
 Mark IMPLAUSIBLE if either of these is true:
 - It is physically or engineering-wise impossible given the components
@@ -150,15 +166,13 @@ Mark IMPLAUSIBLE if either of these is true:
   fatiguing a hull over time is a real structural risk, not just "explosives
   are dangerous in general"; a fuel that's fine in the open becoming
   concentrated in a sealed tube is a real risk, not just "fuel is
-  flammable"). A low given safety score is a signal the pipeline already
-  found something concerning — treat it as evidence, not noise to explain
-  away.
+  flammable").
 - Or: a real regulatory/infrastructure barrier with no plausible workaround.
 
 None of these make something implausible on their own:
 - being unoriginal or something like it already exists
 - being expensive, slow, or short-range
-- a single mediocre score on one metric that isn't safety-related
+- a single mediocre score on one metric
 
 Most concepts that reach this review are ordinary and workable; reserve
 IMPLAUSIBLE for a real, specific problem you can name — but don't require
@@ -167,14 +181,26 @@ Reason from the physics and engineering actually described here, not from
 whether something like it already exists — novelty or lack of it is not
 evidence either way.
 
+## Overall Rating
+Separately from the plausibility verdict, give ONE holistic rating —
+LOW, MEDIUM, or HIGH — for how good this combination is overall. This is a
+single combined judgment, not a separate score per attribute: weigh the
+metric scores above together with your own qualitative read on safety and
+accessibility into one rating, the way a person sizing up the whole concept
+would, not a checklist of independent numbers.
+
 ## What to write
 In 2-4 sentences, give your reasoning, then check it against the scores
-above: if your reasoning conflicts with a score (e.g. you believe this is
-hazardous but its safety score is high), name the metric and say so
+above: if your reasoning conflicts with a score (e.g. you believe cost is
+a serious problem but its cost score is high), name the metric and say so
 explicitly — don't silently contradict a given score.
 
-Finish with exactly one line:
+Finish with exactly two lines. For the first, pick exactly one:
+RATING: LOW
+RATING: MEDIUM
+RATING: HIGH
+
+Then, for the second, pick exactly one:
 VERDICT: PLAUSIBLE
-or
 VERDICT: IMPLAUSIBLE
 """

src/physcom/llm/providers/gemini.py

@@ -13,7 +13,7 @@ from physcom.llm.prompts import (
     format_metrics_for_prompt,
     format_scores_for_prompt,
 )
-from physcom.models.domain import MetricBound
+from physcom.models.domain import Domain, MetricBound
 
 
 class GeminiLLMProvider(LLMProvider):
@@ -51,12 +51,14 @@ class GeminiLLMProvider(LLMProvider):
         combination_description: str,
         raw_metrics: dict[str, float],
         normalized_scores: dict[str, float],
-        metrics: list[MetricBound],
+        domain: Domain,
     ) -> tuple[str, bool]:
-        scores_str = format_scores_for_prompt(raw_metrics, normalized_scores, metrics)
+        scores_str = format_scores_for_prompt(raw_metrics, normalized_scores, domain.metric_bounds)
         prompt = PLAUSIBILITY_REVIEW_PROMPT.format(
             description=combination_description,
             scores=scores_str,
+            domain_name=domain.name,
+            domain_description=domain.description,
         )
         try:
             response = self._client.models.generate_content(

src/physcom/llm/providers/mock.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 from physcom.llm.base import LLMProvider
-from physcom.models.domain import MetricBound
+from physcom.models.domain import Domain, MetricBound
 
 
 class MockLLMProvider(LLMProvider):
@@ -25,7 +25,7 @@ class MockLLMProvider(LLMProvider):
         combination_description: str,
         raw_metrics: dict[str, float],
         normalized_scores: dict[str, float],
-        metrics: list[MetricBound],
+        domain: Domain,
     ) -> tuple[str, bool]:
         avg = sum(normalized_scores.values()) / max(len(normalized_scores), 1)
         if avg > 0.5:

src/physcom/llm/providers/ollama.py

@@ -14,7 +14,7 @@ from physcom.llm.prompts import (
     format_metrics_for_prompt,
     format_scores_for_prompt,
 )
-from physcom.models.domain import MetricBound
+from physcom.models.domain import Domain, MetricBound
 
 
 class OllamaLLMProvider(LLMProvider):
@@ -39,12 +39,14 @@ class OllamaLLMProvider(LLMProvider):
         combination_description: str,
         raw_metrics: dict[str, float],
         normalized_scores: dict[str, float],
-        metrics: list[MetricBound],
+        domain: Domain,
     ) -> tuple[str, bool]:
-        scores_str = format_scores_for_prompt(raw_metrics, normalized_scores, metrics)
+        scores_str = format_scores_for_prompt(raw_metrics, normalized_scores, domain.metric_bounds)
         prompt = PLAUSIBILITY_REVIEW_PROMPT.format(
             description=combination_description,
             scores=scores_str,
+            domain_name=domain.name,
+            domain_description=domain.description,
         )
         text = self._generate(prompt, json_mode=False).strip()
         return (text, parse_verdict(text))

src/physcom/seed/transport_example.py

@@ -728,11 +728,22 @@ URBAN_COMMUTING = Domain(
     name="urban_commuting",
     description="Daily travel within a city, 1-50km range",
     metric_bounds=[
-        MetricBound("power_density", weight=0.25, norm_min=1, norm_max=2000, unit="W/kg"),
-        MetricBound("cost_efficiency", weight=0.25, norm_min=1e-5, norm_max=2e-3, unit="$/m", lower_is_better=True),
-        MetricBound("safety", weight=0.25, norm_min=0.0, norm_max=1.0, unit="0-1"),
-        MetricBound("availability", weight=0.15, norm_min=0.0, norm_max=1.0, unit="0-1"),
-        MetricBound("range_fuel", weight=0.10, norm_min=5000, norm_max=500000, unit="m"),
+        # safety and availability removed from the scored/weighted metric set:
+        # both are judgment calls (risk assessment, infrastructure prevalence),
+        # not physics quantities with a formula, and running them through the
+        # same log-normalize() built for physical quantities produced
+        # incoherent results (a safety raw value already declared as "0-1"
+        # getting re-normalized into a different, unexplainable 0-1 number --
+        # see combo 1540's review, where phi4 could only cite the post-
+        # normalization number with no way to justify it). Safety is now a
+        # qualitative consideration folded into pass 4's holistic RATING
+        # instead. Availability needs real per-infrastructure-type research
+        # this project hasn't done -- not scored anywhere for now rather than
+        # pretend a quick formula or an equally uninformed LLM guess settles it.
+        # Weights renormalized to sum to 1.0 across the remaining metrics.
+        MetricBound("power_density", weight=0.4167, norm_min=1, norm_max=2000, unit="W/kg"),
+        MetricBound("cost_efficiency", weight=0.4167, norm_min=1e-5, norm_max=2e-3, unit="$/m", lower_is_better=True),
+        MetricBound("range_fuel", weight=0.1666, norm_min=5000, norm_max=500000, unit="m"),
     ],
     constraints=[DomainConstraint("medium", ["ground", "air"])],
 )
@@ -741,11 +752,12 @@ INTERPLANETARY = Domain(
     name="interplanetary_travel",
     description="Travel between planets within a solar system",
     metric_bounds=[
-        MetricBound("power_density", weight=0.30, norm_min=10, norm_max=10000, unit="W/kg"),
-        MetricBound("range_fuel", weight=0.30, norm_min=1e9, norm_max=1e13, unit="m"),
-        MetricBound("safety", weight=0.20, norm_min=0.0, norm_max=1.0, unit="0-1"),
-        MetricBound("cost_efficiency", weight=0.10, norm_min=1.0, norm_max=1e6, unit="$/m", lower_is_better=True),
-        MetricBound("range_degradation", weight=0.10, norm_min=8640000, norm_max=3.1536e9, unit="s"),
+        # safety removed -- see URBAN_COMMUTING comment above. Weights
+        # renormalized across the remaining metrics.
+        MetricBound("power_density", weight=0.375, norm_min=10, norm_max=10000, unit="W/kg"),
+        MetricBound("range_fuel", weight=0.375, norm_min=1e9, norm_max=1e13, unit="m"),
+        MetricBound("cost_efficiency", weight=0.125, norm_min=1.0, norm_max=1e6, unit="$/m", lower_is_better=True),
+        MetricBound("range_degradation", weight=0.125, norm_min=8640000, norm_max=3.1536e9, unit="s"),
     ],
     constraints=[DomainConstraint("medium", ["space"])],
 )
@@ -754,11 +766,12 @@ MARITIME_SHIPPING = Domain(
     name="maritime_shipping",
     description="Ocean cargo transport between ports, 100-40000km range",
     metric_bounds=[
-        MetricBound("power_density", weight=0.15, norm_min=1, norm_max=1000, unit="W/kg"),
-        MetricBound("cargo_capacity", weight=0.25, norm_min=1000, norm_max=2e8, unit="kg"),
-        MetricBound("cost_efficiency", weight=0.25, norm_min=1e-9, norm_max=1e-6, unit="$/(kg\u00b7m)", lower_is_better=True),
-        MetricBound("safety", weight=0.20, norm_min=0.0, norm_max=1.0, unit="0-1"),
-        MetricBound("range_fuel", weight=0.15, norm_min=100000, norm_max=40000000, unit="m"),
+        # safety removed -- see URBAN_COMMUTING comment above. Weights
+        # renormalized across the remaining metrics.
+        MetricBound("power_density", weight=0.1875, norm_min=1, norm_max=1000, unit="W/kg"),
+        MetricBound("cargo_capacity", weight=0.3125, norm_min=1000, norm_max=2e8, unit="kg"),
+        MetricBound("cost_efficiency", weight=0.3125, norm_min=1e-9, norm_max=1e-6, unit="$/(kg\u00b7m)", lower_is_better=True),
+        MetricBound("range_fuel", weight=0.1875, norm_min=100000, norm_max=40000000, unit="m"),
     ],
     constraints=[DomainConstraint("medium", ["water"])],
 )
@@ -767,11 +780,12 @@ LAST_MILE_DELIVERY = Domain(
     name="last_mile_delivery",
     description="Short-range package delivery within neighborhoods, 0.5-15km",
     metric_bounds=[
-        MetricBound("power_density", weight=0.25, norm_min=1, norm_max=500, unit="W/kg"),
-        MetricBound("cost_efficiency", weight=0.30, norm_min=1e-5, norm_max=5e-3, unit="$/m", lower_is_better=True),
-        MetricBound("cargo_capacity_kg", weight=0.20, norm_min=1, norm_max=500, unit="kg"),
-        MetricBound("safety", weight=0.15, norm_min=0.0, norm_max=1.0, unit="0-1"),
-        MetricBound("environmental_impact", weight=0.10, norm_min=0, norm_max=5e-4, unit="kg/m", lower_is_better=True),
+        # safety removed -- see URBAN_COMMUTING comment above. Weights
+        # renormalized across the remaining metrics.
+        MetricBound("power_density", weight=0.2941, norm_min=1, norm_max=500, unit="W/kg"),
+        MetricBound("cost_efficiency", weight=0.3529, norm_min=1e-5, norm_max=5e-3, unit="$/m", lower_is_better=True),
+        MetricBound("cargo_capacity_kg", weight=0.2353, norm_min=1, norm_max=500, unit="kg"),
+        MetricBound("environmental_impact", weight=0.1177, norm_min=0, norm_max=5e-4, unit="kg/m", lower_is_better=True),
     ],
     constraints=[DomainConstraint("medium", ["ground", "air"])],
 )
@@ -839,12 +853,11 @@ def load_transport_seed(repo) -> dict:
             counts["domains"] += 1
         except sqlite3.IntegrityError:
             pass
-        # Backfill metric units and lower_is_better on existing DBs.
-        for mb in domain.metric_bounds:
-            repo.ensure_metric(mb.metric_name, unit=mb.unit)
-            repo.backfill_metric_unit(domain.name, mb.metric_name, mb.unit)
-            if mb.lower_is_better:
-                repo.backfill_lower_is_better(domain.name, mb.metric_name)
+        # Sync domain_metric_weights to exactly match this domain's current
+        # metric_bounds on existing DBs -- upserts weight/norm_min/norm_max/
+        # unit for current metrics and removes any that were dropped (e.g.
+        # safety/availability no longer scored).
+        repo.sync_domain_metric_weights(domain)
         # Backfill domain constraints
         repo.replace_domain_constraints(domain)
 

src/physcom_web/routes/results.py

@@ -4,11 +4,25 @@ from __future__ import annotations
 
 from flask import Blueprint, flash, redirect, render_template, request, url_for
 
+from physcom.engine.constraint_resolver import ConstraintResolver
+from physcom.engine.pipeline import Pipeline
+from physcom.engine.scorer import Scorer
 from physcom_web.app import get_repo
 
 bp = Blueprint("results", __name__, url_prefix="/results")
 
 
+def _run_evaluate(repo, domain, combo, platform_mass=None, actuator_mass=None, storage_mass=None):
+    """Purely exploratory -- never writes to the DB. Returns None if this
+    combo has no free mass allocation to explore (see
+    Pipeline.evaluate_allocation's docstring)."""
+    pipeline = Pipeline(repo, ConstraintResolver(), Scorer(domain))
+    return pipeline.evaluate_allocation(
+        combo, domain,
+        platform_mass=platform_mass, actuator_mass=actuator_mass, storage_mass=storage_mass,
+    )
+
+
 @bp.route("/")
 def results_index():
     repo = get_repo()
@@ -25,9 +39,11 @@ def results_domain(domain_name: str):
         return redirect(url_for("results.results_index"))
 
     status_filter = request.args.get("status")
-    results = repo.get_all_results(domain_name, status=status_filter)
+    rating_filter = request.args.get("rating")
+    results = repo.get_all_results(domain_name, status=status_filter, rating=rating_filter)
     # Domain-scoped status counts (only combos that have results in this domain)
     statuses = repo.count_combinations_by_status(domain_name=domain_name)
+    ratings = repo.count_results_by_rating(domain_name)
 
     return render_template(
         "results/list.html",
@@ -35,7 +51,9 @@ def results_domain(domain_name: str):
         domain=domain,
         results=results,
         status_filter=status_filter,
+        rating_filter=rating_filter,
         statuses=statuses,
+        ratings=ratings,
         total_results=sum(statuses.values()),
     )
 
@@ -58,6 +76,7 @@ def result_detail(domain_name: str, combo_id: int):
         flash("No results for this combination in this domain.", "error")
         return redirect(url_for("results.results_domain", domain_name=domain_name))
     scores = repo.get_combination_scores(combo_id, domain.id)
+    explore_result = _run_evaluate(repo, domain, combo)
 
     return render_template(
         "results/detail.html",
@@ -65,6 +84,40 @@ def result_detail(domain_name: str, combo_id: int):
         combo=combo,
         result=result,
         scores=scores,
+        explore_result=explore_result,
+    )
+
+
+@bp.route("/<domain_name>/<int:combo_id>/explore", methods=["POST"])
+def explore(domain_name: str, combo_id: int):
+    """Live, purely exploratory re-evaluation for an explicit platform/
+    actuator/storage mass choice -- never touches stored data. Returns an
+    HTMX partial."""
+    repo = get_repo()
+    domain = repo.get_domain(domain_name)
+    combo = repo.get_combination(combo_id) if domain else None
+    if not domain or not combo:
+        return "", 404
+
+    def _mass(field: str) -> float | None:
+        raw = request.form.get(field)
+        if raw is None:
+            return None
+        try:
+            return float(raw)
+        except ValueError:
+            return None
+
+    explore_result = _run_evaluate(
+        repo, domain, combo,
+        platform_mass=_mass("platform_mass"),
+        actuator_mass=_mass("actuator_mass"),
+        storage_mass=_mass("storage_mass"),
+    )
+    return render_template(
+        "results/_explore_result.html",
+        domain=domain,
+        explore_result=explore_result,
     )
 
 
@@ -101,6 +154,7 @@ def submit_review(domain_name: str, combo_id: int):
         novelty_flag=novelty_flag,
         llm_review=existing.get("llm_review") if existing else None,
         human_notes=human_notes,
+        qualitative_rating=existing.get("qualitative_rating") if existing else None,
     )
     repo.update_combination_status(combo_id, "reviewed")
 

src/physcom_web/static/style.css

@@ -214,6 +214,9 @@ table.compact th, table.compact td { padding: 0.25rem 0.4rem; font-size: 0.83rem
 .badge-llm_reviewed { background: rgba(107,163,160,0.12); color: var(--accent-teal); border-color: rgba(107,163,160,0.25); }
 .badge-reviewed  { background: rgba(155,142,196,0.12); color: var(--accent-violet); border-color: rgba(155,142,196,0.25); }
 .badge-pending   { background: rgba(184,147,92,0.12);  color: var(--accent-amber);  border-color: rgba(184,147,92,0.25); }
+.badge-rating-low    { background: rgba(184,92,92,0.12);   color: var(--accent-red);    border-color: rgba(184,92,92,0.25); }
+.badge-rating-medium { background: rgba(184,147,92,0.12);  color: var(--accent-amber);  border-color: rgba(184,147,92,0.25); }
+.badge-rating-high   { background: rgba(122,171,138,0.12); color: var(--accent-green);  border-color: rgba(122,171,138,0.25); }
 
 /* ── Buttons ─────────────────────────────────────────────── */
 .btn {
@@ -461,6 +464,52 @@ dd { font-size: 0.9rem; color: var(--text-primary); }
   margin-left: 0.3rem;
 }
 
+/* ── Mass allocation bar (optimizer) ───────────────────────── */
+.mass-bar-container {
+  display: flex;
+  width: 100%;
+  height: 18px;
+  border-radius: 4px;
+  overflow: hidden;
+  border: 1px solid var(--border-subtle);
+  margin-top: 0.5rem;
+}
+.mass-bar-seg { height: 100%; }
+.mass-bar-platform { background: var(--accent-blue); }
+.mass-bar-actuator { background: var(--accent-gold); }
+.mass-bar-storage   { background: var(--accent-teal); }
+.mass-bar-legend {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.25rem 1rem;
+  font-size: 0.8rem;
+  color: var(--text-muted);
+  margin-top: 0.4rem;
+  align-items: center;
+}
+.mass-swatch {
+  display: inline-block;
+  width: 10px;
+  height: 10px;
+  border-radius: 2px;
+  margin-right: 0.35rem;
+  vertical-align: middle;
+}
+.optimize-summary { margin-bottom: 0.25rem; }
+.optimize-score { display: flex; flex-direction: column; gap: 0.1rem; }
+
+/* ── Importance sliders (optimizer) ────────────────────────── */
+.weight-slider-row {
+  display: grid;
+  grid-template-columns: 140px 1fr 48px;
+  align-items: center;
+  gap: 0.75rem;
+  margin-bottom: 0.5rem;
+}
+.weight-slider-row label { font-size: 0.85rem; color: var(--text-muted); }
+.weight-slider-row output { font-size: 0.85rem; text-align: right; font-variant-numeric: tabular-nums; }
+.weight-slider-row input[type="range"] { width: 100%; }
+
 /* ── Select dropdown dark styling ────────────────────────── */
 select option {
   background: var(--bg-surface);

src/physcom_web/templates/home.html

@@ -50,12 +50,13 @@
     <div class="step-body">
       <h3>Physics Estimation</h3>
       <p>
-        Surviving combinations get raw metric estimates &mdash; speed, cost,
-        safety, range &mdash; via heuristic stubs or an LLM provider that
-        reasons about the physical properties of each pairing.
+        Surviving combinations get raw metric estimates &mdash; power
+        density, cost, range &mdash; from a deterministic physics engine
+        that sizes each combination from its own declared attributes, not
+        a guess.
       </p>
       <div class="step-example">
-        Bicycle + Human Pedalling &rarr; speed: 20 km/h, cost: $0.01/km
+        Bicycle + Human Muscle &rarr; power density: 4.4 W/kg, range: 500km
       </div>
     </div>
   </div>
@@ -72,8 +73,8 @@
         Combinations are ranked within their domain.
       </p>
       <div class="step-example">
-        Domain <code>urban_commuting</code> weights: speed 25%, cost 25%,
-        safety 25%, availability 15%, range 10%
+        Domain <code>urban_commuting</code> weights: power density 42%,
+        cost 42%, range 17%
       </div>
     </div>
   </div>
@@ -85,9 +86,11 @@
     <div class="step-body">
       <h3>LLM Review</h3>
       <p>
-        Top-scoring combinations are sent to a language model for plausibility
-        and novelty assessment &mdash; catching physically valid but practically
-        absurd pairings.
+        Top-scoring combinations are sent to a language model for a
+        plausibility verdict plus a holistic LOW/MEDIUM/HIGH rating &mdash;
+        weighing safety and accessibility as qualitative judgment calls
+        alongside the physics scores, catching physically valid but
+        practically absurd pairings.
       </p>
       <div class="step-example">
         "Train + Solar Sail: structurally valid constraints, but solar radiation
@@ -163,14 +166,15 @@
   <div class="card concept-card">
     <h3>Metrics</h3>
     <p>
-      Quantitative axes like speed, cost, safety, and range. Each metric
-      has a domain-specific weight and normalization range. Some are
-      inverted &mdash; lower cost is better.
+      Quantitative physics axes like power density, cost, and range. Each
+      metric has a domain-specific weight and normalization range. Some
+      are inverted &mdash; lower cost is better. Safety and accessibility
+      are judgment calls, not physics quantities &mdash; they're weighed
+      qualitatively in the LLM review pass instead of scored here.
     </p>
     <div class="concept-examples">
-      <span class="badge">speed</span>
+      <span class="badge">power_density</span>
       <span class="badge">cost_efficiency</span>
-      <span class="badge">safety</span>
       <span class="badge">range_fuel</span>
     </div>
   </div>

src/physcom_web/templates/results/_explore_result.html

@@ -0,0 +1,55 @@
+{% if explore_result is none %}
+<p class="empty">No free mass allocation to explore for this combination — its
+actuator's mass isn't a design choice (a physiological or footprint-derived
+quantity), or the platform has no declared mass ceiling to bound the sliders.</p>
+{% else %}
+{% set r = explore_result %}
+<div class="optimize-summary">
+  <div class="optimize-score">
+    <span class="score-cell" style="font-size:1.4rem">{{ "%.4f"|format(r.composite_score) }}</span>
+    <span class="subtitle">composite score at this build</span>
+  </div>
+</div>
+
+{% if r.exceeds_platform_envelope %}
+<p class="badge badge-p1_fail" style="display:inline-block;margin-bottom:0.75rem">
+  ⚠ total mass {{ "%.1f"|format(r.total_mass) }}kg exceeds this platform's declared ceiling
+  ({{ "%.1f"|format(r.platform_max) }}kg) — not a build this platform category could carry
+</p>
+{% endif %}
+{% if r.insufficient_structure %}
+<p class="badge badge-p1_fail" style="display:inline-block;margin-bottom:0.75rem">
+  ⚠ platform mass {{ "%.1f"|format(r.platform_mass) }}kg is too little structure to carry
+  {{ "%.1f"|format(r.actuator_mass + r.storage_mass) }}kg of actuator+storage
+</p>
+{% endif %}
+
+<div class="mass-bar-container" title="platform {{ '%.1f'|format(r.platform_mass) }}kg / actuator {{ '%.1f'|format(r.actuator_mass) }}kg / storage {{ '%.1f'|format(r.storage_mass) }}kg">
+  {% set total = r.total_mass %}
+  <div class="mass-bar-seg mass-bar-platform" style="width: {{ (r.platform_mass / total * 100)|round(1) }}%"></div>
+  <div class="mass-bar-seg mass-bar-actuator" style="width: {{ (r.actuator_mass / total * 100)|round(1) }}%"></div>
+  <div class="mass-bar-seg mass-bar-storage" style="width: {{ (r.storage_mass / total * 100)|round(1) }}%"></div>
+</div>
+<div class="mass-bar-legend">
+  <span><span class="mass-swatch mass-bar-platform"></span>platform {{ "%.1f"|format(r.platform_mass) }}kg</span>
+  <span><span class="mass-swatch mass-bar-actuator"></span>actuator {{ "%.1f"|format(r.actuator_mass) }}kg</span>
+  <span><span class="mass-swatch mass-bar-storage"></span>storage {{ "%.1f"|format(r.storage_mass) }}kg</span>
+  <span class="subtitle">{{ "%.1f"|format(r.total_mass) }}kg total</span>
+</div>
+
+<table class="compact" style="margin-top:0.75rem">
+  <thead><tr><th>Metric</th><th>Raw Value</th><th>Normalized</th><th>Weight</th></tr></thead>
+  <tbody>
+    {% for mb in domain.metric_bounds %}
+    {% set val = r.raw_metrics.get(mb.metric_name) %}
+    {% set n = r.normalized_scores.get(mb.metric_name) %}
+    <tr>
+      <td>{{ mb.metric_name }}</td>
+      <td class="score-cell">{{ val|qty(mb.unit) if val is not none else '—' }}</td>
+      <td class="score-cell">{{ "%.4f"|format(n) if n is not none else '—' }}</td>
+      <td>{{ "%.0f%%"|format(mb.weight * 100) }}{{ ' ↓' if mb.lower_is_better else '' }}</td>
+    </tr>
+    {% endfor %}
+  </tbody>
+</table>
+{% endif %}

src/physcom_web/templates/results/detail.html

@@ -27,6 +27,9 @@
     {% if result %}
     <dt>Composite Score</dt><dd class="score-cell">{{ "%.4f"|format(result.composite_score) }}</dd>
     <dt>Pass Reached</dt><dd>{{ result.pass_reached }}</dd>
+    {% if result.qualitative_rating %}
+    <dt>Rating</dt><dd><span class="badge badge-rating-{{ result.qualitative_rating|lower }}">{{ result.qualitative_rating }}</span></dd>
+    {% endif %}
     {% if result.novelty_flag %}
     <dt>Novelty</dt><dd>{{ result.novelty_flag }}</dd>
     {% endif %}
@@ -102,11 +105,16 @@
             {%- elif s.raw_value >= mb.norm_max -%}
               <span class="badge badge-{{ 'p1_fail' if mb.lower_is_better else 'valid' }}">at/above max{{ ' (worst)' if mb.lower_is_better else '' }}</span>
             {%- else -%}
-              {% set pct = ((s.raw_value - mb.norm_min) / (mb.norm_max - mb.norm_min) * 100) | int %}
+              {% set raw_pct = (s.raw_value - mb.norm_min) / (mb.norm_max - mb.norm_min) * 100 %}
+              {# For lower_is_better metrics, raw_pct alone measures distance from norm_min,
+                 not quality -- a value near norm_min (excellent, cost near its floor) would
+                 otherwise render as a near-empty bar. Invert so the bar and percentage always
+                 mean "how good", matching the normalized score's own higher-is-better convention. #}
+              {% set pct = ((100 - raw_pct) if mb.lower_is_better else raw_pct) | int %}
               <div class="metric-bar-container">
                 <div class="metric-bar" style="width: {{ pct }}%"></div>
               </div>
-              <span class="metric-bar-label">~{{ pct }}%{{ ' ↓' if mb.lower_is_better else '' }}</span>
+              <span class="metric-bar-label">~{{ pct }}%{{ ' (lower is better)' if mb.lower_is_better else '' }}</span>
             {%- endif -%}
           {%- else -%}
             —
@@ -121,6 +129,51 @@
 </div>
 {% endif %}
 
+{% if explore_result is not none %}
+<h2>Explore: Scale the Build</h2>
+<p class="subtitle">
+  Purely exploratory — nothing here is saved. Drag a slider to pick a
+  platform weight class, motor size, or battery size directly, and see how
+  power density, range, and the resulting score respond. Sliders open on
+  the saved build above, which is already the score-optimized allocation
+  for this domain (subject to the platform's physical performance floor),
+  so the starting point is the best build already found, not an arbitrary
+  or merely functional one.
+</p>
+<div class="card">
+  {% set r = explore_result %}
+  <form id="explore-form"
+        hx-post="{{ url_for('results.explore', domain_name=domain.name, combo_id=combo.id) }}"
+        hx-trigger="input changed delay:200ms"
+        hx-target="#explore-result" hx-swap="innerHTML">
+    <div class="weight-slider-row">
+      <label for="platform_mass">platform (weight class)</label>
+      <input type="range" min="{{ r.platform_min }}" max="{{ r.platform_max }}" step="0.1"
+             id="platform_mass" name="platform_mass" value="{{ r.platform_mass }}"
+             oninput="document.getElementById('out_platform_mass').textContent = (+this.value).toFixed(1) + 'kg'">
+      <output id="out_platform_mass">{{ "%.1f"|format(r.platform_mass) }}kg</output>
+    </div>
+    <div class="weight-slider-row">
+      <label for="actuator_mass">actuator (motor size)</label>
+      <input type="range" min="{{ r.actuator_min }}" max="{{ r.actuator_slider_max }}" step="0.1"
+             id="actuator_mass" name="actuator_mass" value="{{ r.actuator_mass }}"
+             oninput="document.getElementById('out_actuator_mass').textContent = (+this.value).toFixed(1) + 'kg'">
+      <output id="out_actuator_mass">{{ "%.1f"|format(r.actuator_mass) }}kg</output>
+    </div>
+    <div class="weight-slider-row">
+      <label for="storage_mass">storage (battery/tank size)</label>
+      <input type="range" min="{{ r.storage_min }}" max="{{ r.storage_slider_max }}" step="0.1"
+             id="storage_mass" name="storage_mass" value="{{ r.storage_mass }}"
+             oninput="document.getElementById('out_storage_mass').textContent = (+this.value).toFixed(1) + 'kg'">
+      <output id="out_storage_mass">{{ "%.1f"|format(r.storage_mass) }}kg</output>
+    </div>
+  </form>
+  <div id="explore-result">
+    {% include "results/_explore_result.html" %}
+  </div>
+</div>
+{% endif %}
+
 <h2>Human Review</h2>
 <div id="review-section">
   {% include "results/_review_form.html" %}

src/physcom_web/templates/results/list.html

@@ -26,11 +26,11 @@
 
   {% if statuses %}
   <div class="filter-row">
-    <span>Filter:</span>
-    <a href="{{ url_for('results.results_domain', domain_name=domain.name) }}"
+    <span>Status:</span>
+    <a href="{{ url_for('results.results_domain', domain_name=domain.name, rating=rating_filter) }}"
        class="btn btn-sm {{ '' if status_filter else 'btn-primary' }}">All ({{ total_results }})</a>
     {% for s, cnt in statuses.items() %}
-    <a href="{{ url_for('results.results_domain', domain_name=domain.name, status=s) }}"
+    <a href="{{ url_for('results.results_domain', domain_name=domain.name, status=s, rating=rating_filter) }}"
        class="btn btn-sm {{ 'btn-primary' if status_filter == s else '' }}">
       {{ s }} ({{ cnt }})
     </a>
@@ -38,9 +38,25 @@
   </div>
   {% endif %}
 
+  {% if ratings %}
+  <div class="filter-row">
+    <span>Rating:</span>
+    <a href="{{ url_for('results.results_domain', domain_name=domain.name, status=status_filter) }}"
+       class="btn btn-sm {{ '' if not rating_filter else 'btn-primary' }}">All</a>
+    {% for rt in ['HIGH', 'MEDIUM', 'LOW'] %}
+    {% if rt in ratings %}
+    <a href="{{ url_for('results.results_domain', domain_name=domain.name, status=status_filter, rating=rt) }}"
+       class="btn btn-sm {{ 'btn-primary' if rating_filter == rt else '' }}">
+      {{ rt }} ({{ ratings[rt] }})
+    </a>
+    {% endif %}
+    {% endfor %}
+  </div>
+  {% endif %}
+
   {% if not results %}
-    {% if status_filter %}
-    <p class="empty">No results with status "{{ status_filter }}" in this domain.</p>
+    {% if status_filter or rating_filter %}
+    <p class="empty">No results matching that filter in this domain.</p>
     {% else %}
     <p class="empty">No results for this domain yet. <a href="{{ url_for('pipeline.pipeline_form') }}">Run the pipeline</a> first.</p>
     {% endif %}
@@ -52,6 +68,7 @@
         <th>Score</th>
         <th>Entities</th>
         <th>Status</th>
+        <th>Rating</th>
         <th>Details</th>
         <th></th>
       </tr>
@@ -69,6 +86,13 @@
             <span class="badge badge-{{ r.combination.status }}">{{ r.combination.status }}</span>
           {%- endif -%}
         </td>
+        <td>
+          {%- if r.qualitative_rating -%}
+            <span class="badge badge-rating-{{ r.qualitative_rating|lower }}">{{ r.qualitative_rating }}</span>
+          {%- else -%}
+            —
+          {%- endif -%}
+        </td>
         <td class="block-reason-cell">
           {%- if r.domain_block_reason -%}
             {{ r.domain_block_reason }}

tests/test_pipeline.py

@@ -69,6 +69,12 @@ def test_blocked_combos_not_scored(seeded_repo):
         score_threshold=0.0, passes=[1, 2, 3, 5],
     )
 
-    # Estimated count should be less than total (blocked ones filtered)
+    # Estimated count should be less than total (blocked ones filtered).
+    # Not necessarily equal to pass1_valid + pass1_conditional: a combo can
+    # pass pass 1's entity-declared-floor checks but still turn out
+    # structurally infeasible once pass 2 solves the domain-specific
+    # actuator/storage requirement (e.g. an engine too big to fit its own
+    # platform's declared mass ceiling) -- that's a legitimate per-domain
+    # block, not a bug (see Pipeline._decide_masses' `feasible` return).
     assert result.pass2_estimated < result.total_generated
-    assert result.pass2_estimated == result.pass1_valid + result.pass1_conditional
+    assert result.pass2_estimated <= result.pass1_valid + result.pass1_conditional

tests/test_pipeline_async.py

@@ -335,28 +335,34 @@ def test_p3_fail_below_threshold(seeded_repo):
 
 
 def test_p4_fail_implausible(seeded_repo):
-    """Combos deemed implausible by LLM should get p4_fail status."""
+    """Combos deemed implausible by LLM should get p4_fail status.
+
+    Pass 2 is estimator-only now (never calls the LLM), so there's no way
+    to force every combo's raw estimates toward a controlled low/high value
+    the way MockLLMProvider's default_estimates used to. Force the pass-4
+    verdict directly instead -- what's under test here is pipeline.py's
+    wiring of review_plausibility's return value to status/counters, not
+    MockLLMProvider's avg-based heuristic.
+    """
     from physcom.llm.providers.mock import MockLLMProvider
 
+    class AlwaysImplausibleLLM(MockLLMProvider):
+        def review_plausibility(self, description, raw_metrics, normalized_scores, domain):
+            return ("Always implausible for testing.", False)
+
     repo = seeded_repo
     domain = repo.get_domain("urban_commuting")
 
     resolver = ConstraintResolver()
     scorer = Scorer(domain)
-    # Low estimates → normalized scores avg <= 0.5 → MockLLMProvider returns (text, False)
     # Use threshold=0.0 so no combo gets p3_fail and all reach pass 4
-    mock_llm = MockLLMProvider(default_estimates={
-        "power_density": 0.1, "cost_efficiency": 0.1, "safety": 0.1,
-        "availability": 0.1, "range_fuel": 0.1,
-    })
-    pipeline = Pipeline(repo, resolver, scorer, llm=mock_llm)
+    pipeline = Pipeline(repo, resolver, scorer, llm=AlwaysImplausibleLLM())
 
     result = pipeline.run(
         domain, ["platform", "actuator", "energy_storage"],
         score_threshold=0.0, passes=[1, 2, 3, 4],
     )
 
-    # With low normalized scores (avg <= 0.5), reviewed combos should be p4_fail
     assert result.pass4_failed > 0
     assert result.pass4_reviewed == 0
 
@@ -367,20 +373,23 @@ def test_p4_fail_implausible(seeded_repo):
 
 
 def test_p4_pass_plausible(seeded_repo):
-    """Combos deemed plausible by LLM should get llm_reviewed status."""
+    """Combos deemed plausible by LLM should get llm_reviewed status.
+
+    See test_p4_fail_implausible on why the verdict is forced directly
+    rather than via controlled pass-2 estimates.
+    """
     from physcom.llm.providers.mock import MockLLMProvider
 
+    class AlwaysPlausibleLLM(MockLLMProvider):
+        def review_plausibility(self, description, raw_metrics, normalized_scores, domain):
+            return ("Always plausible for testing.", True)
+
     repo = seeded_repo
     domain = repo.get_domain("urban_commuting")
 
     resolver = ConstraintResolver()
     scorer = Scorer(domain)
-    # High estimates → avg > 0.5 → MockLLMProvider returns (text, True)
-    mock_llm = MockLLMProvider(default_estimates={
-        "power_density": 500.0, "cost_efficiency": 5e-4, "safety": 0.6,
-        "availability": 0.7, "range_fuel": 200000.0,
-    })
-    pipeline = Pipeline(repo, resolver, scorer, llm=mock_llm)
+    pipeline = Pipeline(repo, resolver, scorer, llm=AlwaysPlausibleLLM())
 
     result = pipeline.run(
         domain, ["platform", "actuator", "energy_storage"],