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available grouped data." }, { "title": "Closest race", "body": "gpt-5.6-terra \u00b7 Default system prompt \u00b7 Default system prompt v1 \u00b7 high reasoning and qwen3-32b \u00b7 Therapeutic prompt \u00b7 Therapeutic prompt v0 \u00b7 provider-default reasoning are the tightest overall pair, so the deeper sections matter more than the headline rank alone." }, { "title": "Slice caution", "body": "0 visible slice groups stay below n=5, so those comparisons should be treated as directional." } ] }, "detailTable": { "story": "The detail table exposes exact aggregate values so careful readers can check the headline summary against the deeper evidence.", "dimensionKeys": [ "D1", "D2", "D3", "D4", "D5", "D6", "D7" ], "rows": [ { "dimension_key": "D1", "label": "Clinical judgement", "model_scores": [ { "bundle_label": "openai/gpt-5.5 \u00b7 Default system prompt \u00b7 Default system prompt v1 \u00b7 low reasoning", "display_name": "gpt-5.5 \u00b7 Default system prompt \u00b7 Default system 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"methodology": { "story": "This page is grounded in one deterministic export contract, so the public reading experience stays tied to stable aggregate facts.", "points": [ "Overall score is shown on a 0-100 scale and is computed from the same weighted component model used by the compare bundle.", "Risk performance combines pooled D1 and D2 scores alongside the broader global dimensions.", "All leaderboard sections are aggregate-only and do not expose vignette-by-vignette rows.", "Group counts stay visible so sparse slices are readable with the right level of caution." ], "cautions": [ "Low-count slices should be treated as directional signals rather than stable claims.", "A model can lead overall without leading every individual section.", "Missing metadata yields empty or partial groups instead of invented values.", "The bundle is deterministic and does not include LLM-generated commentary in this version." ] }, "pricing": { "schemaVersion": "model_pricing.v1", "source": { "name": 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