feat: redesign around phenotype-driven triage, not variant filtering

A table with filters made the user do the work. Rare disease triage is a different task:
which few variants could explain *this* patient's phenotype, and why. The app now answers
that, and lets a reviewer act on the answer.

Domain
- a case is a proband: a VCF plus the HPO terms observed in the patient (samples -> cases)
- HPO's gene-to-phenotype annotations are loaded as reference data (scripts/load-hpo.py)
- each candidate can be shortlisted or dismissed with a reason and a note

Ranking (app/services/triage.py, 21 tests)
- weighted sum of phenotype match, rarity, consequence severity and the model's score,
  with every component shown next to the candidate
- rarity and consequence filter; phenotype only ranks, because a real diagnosis can sit in
  a gene nobody has annotated yet and filtering on it would hide exactly that case
- ClinVar is deliberately not an input: it appears beside the result as independent
  confirmation, so nothing ranks highly merely because ClinVar already said pathogenic

UI
- the funnel is the headline: variants called -> rare -> coding candidates -> phenotype-matched
- ranked candidates with evidence chips, not a grid of everything; filters are demoted
- a variant panel showing the score breakdown, the matched HPO terms, the raw VEP record and
  links out to Ensembl/gnomAD/ClinVar, with the decision controls
- a printable case report: phenotype, funnel, shortlisted variants with reasons, provenance

API: /cases with phenotypes, /cases/{id}/candidates (funnel + ranked + weights),
/variants/{id}, /variants/{id}/decision, /cases/{id}/report, /phenotypes for the picker.
Scoring moved under the case and now answers 503 with the reason when no model registry is
reachable, instead of a 500.

Verified end to end on a simulated proband (scripts/make-demo-case.sh: real GIAB HG002
background + one real ClinVar 2-star pathogenic NF2 variant). 13 variants called -> 1 coding
candidate, and the planted variant ranks first at 0.80 on phenotype 1.00, rarity 1.00 and
consequence 1.00, with ClinVar agreeing afterwards.

Tests: api 75, ml 18, loader 16, web 27; ruff, mypy, svelte-check, terraform validate, both
kustomize overlays and the Nextflow stub run all clean.

scripts/load-hpo.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+"""Load HPO's gene-to-phenotype annotations into the gene_phenotypes table.
+
+This is the reference data the ranking matches a case's phenotype against. Source file:
+https://purl.obolibrary.org/obo/hp/hpoa/genes_to_phenotype.txt (HPO release, ~20 MB).
+
+Cite the Human Phenotype Ontology when showing results; see docs/data.md.
+"""
+import argparse
+import csv
+import io
+import os
+import sys
+import urllib.request
+
+from sqlalchemy import create_engine, text
+from sqlalchemy.engine import make_url
+
+URL = "https://purl.obolibrary.org/obo/hp/hpoa/genes_to_phenotype.txt"
+
+
+def rows(handle: io.TextIOBase) -> list[tuple[str, str, str]]:
+    """Unique (gene, term) pairs; the file repeats them once per associated disease."""
+    seen: set[tuple[str, str]] = set()
+    out: list[tuple[str, str, str]] = []
+    for row in csv.DictReader(handle, delimiter="\t"):
+        gene, hpo_id, name = row["gene_symbol"], row["hpo_id"], row["hpo_name"]
+        if not gene or not hpo_id or (gene, hpo_id) in seen:
+            continue
+        seen.add((gene, hpo_id))
+        out.append((gene[:60], hpo_id[:20], name[:200]))
+    return out
+
+
+def main() -> None:
+    p = argparse.ArgumentParser()
+    p.add_argument("--url", default=URL)
+    p.add_argument("--file", help="use a local copy instead of downloading")
+    a = p.parse_args()
+
+    url = os.environ.get("DATABASE_URL")
+    if not url:
+        sys.exit("DATABASE_URL is not set")
+
+    if a.file:
+        with open(a.file) as fh:
+            annotations = rows(fh)
+    else:
+        print(f"downloading {a.url}", file=sys.stderr)
+        with urllib.request.urlopen(a.url) as response:  # noqa: S310 - fixed HPO release URL
+            annotations = rows(io.TextIOWrapper(response, encoding="utf-8"))
+    print(f"{len(annotations)} gene/term pairs", file=sys.stderr)
+
+    engine = create_engine(make_url(url).set(drivername="postgresql+psycopg"))
+    with engine.begin() as conn:
+        conn.execute(text("TRUNCATE gene_phenotypes RESTART IDENTITY"))
+        cursor = conn.connection.cursor()
+        with cursor.copy("COPY gene_phenotypes (gene_symbol, hpo_id, hpo_name) FROM STDIN") as copy:
+            for row in annotations:
+                copy.write_row(row)
+    print(f"loaded {len(annotations)} annotations", file=sys.stderr)
+
+
+if __name__ == "__main__":
+    main()