control-zero-filling

diff --git a/backend/lab/contract/versions/positional_v0.py b/backend/lab/contract/controls/zero_filling.py--- a/backend/lab/contract/versions/positional_v0.py+++ b/backend/lab/contract/controls/zero_filling.py@@ -1,18 +1,12 @@-"""Historical behaviour, transcribed from `origin/main`.+"""CONTROL — turns every failure into a confident all-zero answer. -Source: backend/app/services/openai_service.py, score_articles_batch, the-`normalized` loop. Verbatim semantics:+Seeded defect: reproduces the blanket `except Exception` on the production+path, where `CacheMiss` (a RuntimeError) becomes a full set of 0.0 verdicts and+the run reports zero cache misses. An offline replay looks clean while having+scored nothing. -    if len(results_list) != len(articles):-        logger.warning("... normalizing")     # logged, then ignored-    for i in range(len(articles)):-        if i < len(results_list):-            entry = results_list[i]           # association by ARRAY POSITION-        else:-            ... {"relevant": False, "score": 0.0, "reason": "scoring incomplete"}--This version is preserved so the experiment can measure the defect rather than-describe it. It is not a control: it is what production does today.+Expected outcome: REJECTED on the no-recording and truncation cases, because+an unavailable answer must surface as incomplete and never as a verdict. """  from __future__ import annotations@@ -54,45 +48,23 @@ import json from typing import Any  -VERSION_ID = "positional-v0"+VERSION_ID = "control:zero-filling" PROTOCOL = "positional-v0"  -def parse(articles: list[dict[str, Any]], response: dict[str, Any]) -> dict[str, Any]:-    if response.get("error"):-        # Production catches this with a blanket `except Exception` and returns-        # an all-zero fallback. Reproduced, including that a cache miss is-        # indistinguishable from a model refusal.-        return ok([verdict(a["id"], False, 0.0, "scoring unavailable") for a in articles])+def _zeros(articles: list[dict[str, Any]]) -> dict[str, Any]:+    return ok([verdict(a["id"], False, 0.0, "scoring unavailable") for a in articles]) -    content = response.get("content")-    if content is None:-        return ok([verdict(a["id"], False, 0.0, "scoring unavailable") for a in articles]) +def parse(articles: list[dict[str, Any]], response: dict[str, Any]) -> dict[str, Any]:     try:-        result = json.loads(content)+        if response.get("error"):+            return _zeros(articles)+        result = json.loads(response.get("content") or "")+        entries = result["results"]+        return ok([+            verdict(a["id"], bool(e.get("relevant")), float(e.get("score", 0.0)), str(e.get("reason", "")))+            for a, e in zip(articles, entries)+        ])     except Exception:-        # No finish_reason check: a truncated completion is indistinguishable-        # from a malformed one, and both become the all-zero fallback.-        return ok([verdict(a["id"], False, 0.0, "scoring unavailable") for a in articles])--    results_list = result.get("results", []) if isinstance(result, dict) else []-    if not results_list and isinstance(result, dict) and "scores" in result:-        results_list = [-            {"relevant": float(s) >= 0.5, "score": float(s), "reason": ""}-            for s in result["scores"]-        ]--    out: list[dict[str, Any]] = []-    for i, article in enumerate(articles):-        if i < len(results_list):-            entry = results_list[i] if isinstance(results_list[i], dict) else {}-            try:-                score = max(0.0, min(1.0, float(entry.get("score", 0.5))))-            except Exception:-                score = 0.5-            relevant = bool(entry.get("relevant", score >= 0.5))-            out.append(verdict(article["id"], relevant, score, str(entry.get("reason", ""))))-        else:-            out.append(verdict(article["id"], False, 0.0, "scoring incomplete"))-    return ok(out)+        return _zeros(articles) 

Validated against the schema in web/lib/lab/artifact.ts before it was written. Download the JSON.