{ "evaluation_id": "EVAL-20260402-195402", "question_id": "ANALYSIS-017", "question_text": "A pharmaceutical company reports: 'Our drug reduced hospitalization by 50% (p < 0.001). 2% of patients in the treatment group were hospitalized vs 4% in the control group.' (1) Calculate the absolute risk reduction and NNT (number needed to treat). (2) The trial had 200 patients. Is this enough for the claimed significance? (3) The control group received no treatment (not a placebo). Why is this problematic? (4) Side effects occurred in 8% of the treatment group. Should this drug be approved?", "category": "analysis", "timestamp": "2026-04-02T19:54:02.335Z", "display_date": "Apr 02, 2026", "winner": { "name": "GPT-OSS-120B", "provider": "OpenAI", "score": 9.57 }, "avg_score": 8.783334, "matrix_size": 80, "models_used": [ { "id": "claude_opus_46", "name": "Claude Opus 4.6", "provider": "openrouter" }, { "id": "gpt_5_4", "name": "GPT-5.4", "provider": "openrouter" }, { "id": "deepseek_v4", "name": "DeepSeek V4", "provider": "openrouter" }, { "id": "mimo_v2_flash", "name": "MiMo-V2-Flash", "provider": "Xiaomi" }, { "id": "claude_sonnet_46", "name": "Claude Sonnet 4.6", "provider": "openrouter" }, { "id": "grok_420", "name": "Grok 4.20", "provider": "openrouter" }, { "id": "gpt_oss_120b", "name": "GPT-OSS-120B", "provider": "OpenAI" }, { "id": "gemini_31_pro", "name": "Gemini 3.1 Pro", "provider": "openrouter" }, { "id": "gemini_3_flash", "name": "Gemini 3 Flash Preview", "provider": "Google" } ], "rankings": { "gpt_oss_120b": { "display_name": "GPT-OSS-120B", "provider": "OpenAI", "average_score": 9.57, "score_count": 9, "min_score": 8.8, "max_score": 10, "rank": 1 }, "claude_sonnet_46": { "display_name": "Claude Sonnet 4.6", "provider": "openrouter", "average_score": 9.23, "score_count": 9, "min_score": 8.6, "max_score": 10, "rank": 2 }, "grok_420": { "display_name": "Grok 4.20", "provider": "openrouter", "average_score": 9.22, "score_count": 9, "min_score": 8.45, "max_score": 10, "rank": 3 }, "gpt_5_4": { "display_name": "GPT-5.4", "provider": "openrouter", "average_score": 9.16, "score_count": 9, "min_score": 8.65, "max_score": 10, "rank": 4 }, "gemini_3_flash": { "display_name": "Gemini 3 Flash Preview", "provider": "Google", "average_score": 9.03, "score_count": 8, "min_score": 8.8, "max_score": 9.45, "rank": 5 }, "claude_opus_46": { "display_name": "Claude Opus 4.6", "provider": "openrouter", "average_score": 8.97, "score_count": 9, "min_score": 8.2, "max_score": 10, "rank": 6 }, "deepseek_v4": { "display_name": "DeepSeek V4", "provider": "openrouter", "average_score": 8.61, "score_count": 9, "min_score": 7.9, "max_score": 9.8, "rank": 7 }, "mimo_v2_flash": { "display_name": "MiMo-V2-Flash", "provider": "Xiaomi", "average_score": 7.75, "score_count": 9, "min_score": 6.5, "max_score": 9.55, "rank": 8 }, "gemini_31_pro": { "display_name": "Gemini 3.1 Pro", "provider": "openrouter", "average_score": 7.51, "score_count": 9, "min_score": 6.45, "max_score": 8.6, "rank": 9 } }, "judgments": [ { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9.25, "brief_justification": "The response is highly accurate, analytically deep, and well-structured, including excellent statistical calculations. However, the text cuts off at the very end, slightly impacting completeness." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 10, "brief_justification": "Flawless response. The math is perfectly accurate, the statistical reasoning is deep and correct, and the critical appraisal of the trial design is comprehensive. Excellent structure and clarity." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 7.9, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 6.95, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 10, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 10, "brief_justification": "The response is exceptionally accurate, correctly calculating the ARR and NNT, and astutely proving the statistical impossibility of the claimed p-value. It provides deep, clear, and highly useful insights into clinical trial design and risk-benefit analysis." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 10, "brief_justification": "The response is exceptionally accurate, providing precise statistical calculations to disprove the p-value claim. It thoroughly addresses all parts of the prompt with excellent clarity, depth of analysis regarding clinical trial methodology, and practical usefulness in its final recommendation." }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 7.45, "brief_justification": "The ARR and NNT calculations are correct. The analysis of sample size adequacy is excellent and mathematically well-reasoned, correctly identifying that the claimed p-value is implausible with only 200 patients. However, the response is clearly cut off mid-sentence during the placebo discussion (point 3) and entirely missing the analysis of point 4 (side effects and approval recommendation). This significantly impacts completeness. The portions that are present are clear, well-structured, and sh" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9.2, "brief_justification": "The response is factually accurate across all four parts. The ARR and NNT calculations are correct. The power analysis for part 2 is well-reasoned with a concrete z-score approximation showing the claimed p-value is implausible. The discussion of no-treatment vs placebo is thorough, covering blinding, placebo effect, differential attention, and outcome assessment bias. The benefit-harm analysis in part 4 is excellent, introducing NNH and comparing it to NNT. The response is exceptionally well-st" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.25, "brief_justification": "Calculations for ARR and NNT are correct. The power analysis for part 2 is well done with the z-test calculation showing the p-value claim is implausible with 200 patients. Part 3 correctly identifies placebo effect, observer bias, and ethical concerns, though could have elaborated more on Hawthorne effect and nocebo. Part 4 provides a reasonable risk-benefit framework but could have been more quantitative (e.g., NNH = 1/0.08 ≈ 13, meaning for every hospitalization prevented, ~4 patients experie" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 6.9, "brief_justification": "The ARR and NNT calculations are correct. However, the answer to question (2) is fundamentally wrong: with only 4 vs 2 events out of ~100 per group, a Fisher's exact test yields a p-value around 0.4-0.7, nowhere near p < 0.001. The response incorrectly states the sample size is sufficient and that the p-value would be robust, which is a major factual error on a core statistical reasoning question. The discussion of no-placebo control and the approval recommendation are reasonable and well-struct" }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9, "brief_justification": "Excellent, rigorous analysis. Correctly identifies the statistical impossibility of the p-value and provides a detailed bias hierarchy. Minor nitpick: the power calculation assumes a target difference of 0.02, but the calculation is valid for assessing the plausibility of the result." }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.95, "brief_justification": "Excellent, well-structured analysis. ARR and NNT calculations are correct. The power analysis and Fisher's exact test demonstration are strong and approximately correct (the actual p-value from Fisher's exact test for a 2x2 table with those numbers is around 0.4, confirming the claim). The placebo discussion is thorough and well-reasoned. Minor issues: the NNH calculation assumes 0% side effects in the control group, which wasn't stated; the power calculation uses Z_alpha/2 = 3.09 which correspo" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.2, "brief_justification": "The response is exceptionally well-structured and demonstrates deep understanding of biostatistics and clinical trial design. The ARR and NNT calculations are correct. The power analysis for n=200 is well-reasoned — correctly identifying that 6 total events cannot yield p<0.001, with appropriate Fisher's exact test calculation. The discussion of no-treatment control limitations is thorough, covering placebo effect, performance bias, detection bias, and nocebo effect. The risk-benefit analysis co" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.4, "brief_justification": "The response is exceptionally well-structured and thorough. ARR and NNT calculations are correct. The statistical power analysis correctly demonstrates that 200 patients cannot yield p<0.001 with these event rates, showing the actual z-test and Fisher exact test results. The discussion of no-treatment vs placebo control is comprehensive and well-organized. The benefit-risk analysis using NNT vs NNH is insightful. Minor note: the NNH calculation technically assumes 0% side effects in the control " }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.2, "brief_justification": "The response is highly accurate across all four parts. The ARR and NNT calculations are correct. The statistical power analysis in part 2 is well-reasoned—correctly noting that 4 vs 2 events in 200 patients cannot yield p<0.001, with a reasonable approximate p-value cited. The placebo discussion covers the key biases (placebo effect, observer bias, confounding). The approval recommendation is well-argued, correctly highlighting the 8% side effect rate vs 2% ARR imbalance and the misleading natur" }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.45, "brief_justification": "Correctly computes ARR=2% and NNT=50, and rightly questions the p<0.001 claim for 200 patients. However, the response is truncated, so the placebo-control issue and approval recommendation are incomplete. Clear and reasonably insightful, but missing key final judgments." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.2, "brief_justification": "Correctly computes ARR=2% and NNT=50, and rightly questions the p<0.001 claim with only ~2 vs 4 events in 200 patients. Strong discussion of bias from no-placebo/no-blinding. Slight overreach in accusing possible fabrication and in treating side-effect rate as NNH without considering severity or baseline adverse-event rate; final approval recommendation is also truncated." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.8, "brief_justification": "Accurately computes ARR and NNT, correctly challenges the plausibility of p < 0.001 with 2/100 vs 4/100, and explains bias from no-placebo controls well. The approval discussion is appropriately cautious and context-dependent, though it could more explicitly note that side-effect comparison to control and severity data are necessary." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 6.5, "brief_justification": "ARR and NNT are calculated correctly, and the placebo-control critique and approval discussion are reasonably clear. However, the key statistical claim is incorrect: with 200 patients total and event rates of 2% vs 4% (about 2 vs 4 events), p < 0.001 is not plausible; the response wrongly accepts the claimed significance and overstates robustness. Approval reasoning is sensible but somewhat speculative without severity details for side effects and hospitalization." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.75, "brief_justification": "Accurately computes ARR=2% and NNT=50, correctly questions p<0.001 with only 2 vs 4 events, and explains why no-treatment control is biased. Strong risk-benefit discussion and practical approval caution. Minor overstatement in calling relative risk framing a manipulation tactic and in implying placebo could explain hospitalization differences without considering objective endpoints and trial details." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9, "brief_justification": "Accurately computes ARR=2% and NNT=50, correctly questions the plausibility of p<0.001 with only about 2 vs 4 events, explains why no-treatment control introduces major bias, and gives a balanced approval judgment based on weak design and uncertain risk-benefit. Minor caveat: calling p<0.001 literally impossible is slightly too strong without knowing exact allocation/analysis details." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.55, "brief_justification": "Accurately computes ARR=2% and NNT=50, correctly questions the p<0.001 claim for 2 vs 4 events in 200 patients, explains the no-treatment control problem well, and gives a practical benefit-risk judgment. Minor caveat: statements like 'impossible' and regulatory references are a bit stronger than necessary without exact trial details." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Accurately computes ARR=2% and NNT=50, correctly questions the claimed p-value with only ~2 vs 4 events in 200 patients, and explains why no-placebo control can introduce bias. The approval recommendation is well justified, though side effects are discussed somewhat simplistically without distinguishing severity or net clinical benefit." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.6, "brief_justification": "Accurate calculations and insightful analysis, though slightly incomplete on the placebo effect explanation." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.8, "brief_justification": "Detailed and accurate analysis with insightful critique of statistical claims and study design." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.65, "brief_justification": "Highly accurate and thorough response with clear explanations and practical insights." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.65, "brief_justification": "Accurate calculations and thorough analysis with clear explanations, though deeper discussion on side effects could enhance depth." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.8, "brief_justification": "Comprehensive, accurate, and insightful analysis with clear practical implications." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 8.8, "brief_justification": "Accurate calculations, thorough critique of statistical claims, clear explanation of design flaws, and actionable conclusion." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.45, "brief_justification": "Highly accurate, thorough, and insightful with clear practical implications." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.2, "brief_justification": "Accurate calculations, thorough analysis, clear structure, insightful critique, and practical conclusions." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.25, "brief_justification": "The response is highly accurate, particularly in identifying the statistical impossibility of the p-value given the sample size. It correctly calculates ARR and NNT and begins to address the bias issues. It is slightly incomplete as it cuts off mid-sentence on the third point and does not explicitly address the final question regarding approval and side effects." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "Accurate calculations, strong statistical reasoning, and clear identification of trial design flaws. The response effectively balances benefit vs. harm." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 9.2, "brief_justification": "The response is highly accurate, well-structured, and provides deep analysis, particularly in the statistical power calculation and risk-benefit assessment. Minor deduction in correctness for not explicitly checking the math of the provided p-value, but the conclusion is correct." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.55, "brief_justification": "Comprehensive, accurate, and well-structured analysis with strong statistical reasoning and practical recommendations." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.55, "brief_justification": "Accurate calculations, thorough analysis of statistical plausibility, design flaws, and approval considerations; clear structure and actionable insights." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.55, "brief_justification": "Accurate calculations, thorough analysis of all sub-questions, clear structure, insightful risk-benefit assessment, and highly actionable conclusion." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.2, "brief_justification": "Accurate calculations, thorough analysis of statistical and methodological issues, clear structure, and practical recommendations." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 7.25, "brief_justification": "The response is accurate and well-structured for parts 1 and 2, with excellent statistical reasoning about the impossibility of p<0.001 with only 200 patients. However, the response is clearly truncated—it cuts off mid-sentence in part 3 and never addresses part 4 (drug approval decision weighing NNT=50 against 8% side effects). The incomplete coverage significantly reduces completeness and usefulness scores despite strong quality in the portions that were completed." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9.2, "brief_justification": "Exceptional analysis with accurate calculations (ARR=2%, NNT=50), rigorous power analysis correctly identifying the p<0.001 claim as implausible with Fisher's exact test showing p≈0.68, comprehensive bias taxonomy for the no-placebo issue, and a well-structured harm-benefit framework. The LHH ratio calculation adds genuine depth. Minor issue: the response appears truncated at the end, cutting off the final decision section, which slightly reduces completeness. The statistical power calculation i" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9.2, "brief_justification": "Excellent response covering all four questions thoroughly. ARR and NNT calculations are correct. The statistical critique of p<0.001 with 200 patients is well-reasoned with a z-score approximation. The placebo discussion covers blinding, placebo effect, and differential attention. The benefit-harm analysis correctly computes NNH (~12.5) and compares it to NNT (50), showing more harm than benefit. The conclusion is appropriately cautious and evidence-based. Minor gap: could have mentioned that th" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.55, "brief_justification": "The response correctly calculates ARR and NNT, performs a proper z-test showing the p-value claim is unsupported, identifies key placebo-related biases, and provides a nuanced risk-benefit analysis. The statistical work in part 2 is particularly strong. Minor gaps include not mentioning regression to the mean or the Hawthorne effect in part 3, and not quantifying the side effect burden relative to benefit more explicitly in part 4 (e.g., noting 8% side effects vs 2% absolute benefit is a concern" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.3, "brief_justification": "The response is well-structured and covers all four questions thoroughly. The ARR and NNT calculations are correct. However, the claim that p<0.001 is achievable with only 6 total events (2 vs 4) is incorrect—this would not yield p<0.001 with a chi-square or Fisher's exact test; the actual p-value would be much larger (around 0.6-0.7), making the claimed significance implausible. The response should have flagged this as a red flag rather than validating it. The placebo discussion is good, coveri" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9, "brief_justification": "Excellent response covering all four parts thoroughly. The statistical analysis is accurate and well-explained, correctly identifying the impossibility of p<0.001 with only 6 events. The Fisher's exact test p-value approximation (~0.68) is reasonable. The discussion of placebo vs no-treatment bias is comprehensive. The risk-benefit analysis is insightful, noting that 8% side effects vs 2% ARR means 4 patients harmed per 1 helped. Minor point: could have mentioned that the p-value calculation ass" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.55, "brief_justification": "Excellent response covering all four questions with precise calculations, statistical verification showing the p<0.001 claim is impossible with these numbers, thorough methodological critique of the no-placebo control, and a well-reasoned benefit-harm analysis using NNT/NNH comparison. The summary table adds practical value. Minor note: the NNH calculation assumes 8% side effects vs 0% in control, which isn't stated but is a reasonable assumption given the context." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Excellent response covering all four parts accurately. ARR and NNT calculations are correct. The statistical analysis is particularly strong, correctly identifying that 4 vs 2 events yields p≈0.68, not p<0.001. Placebo discussion covers key biases well. The approval recommendation is well-reasoned with the 4x harm-to-benefit ratio being a compelling insight. Minor gap: could mention severity/nature of side effects matters for approval decisions, and that NNT=50 context depends on disease severit" }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.05, "brief_justification": "Accurate calculations and strong statistical critique on sample size and p-value impossibility; good explanation of placebo issue though response is truncated. Provides practical insights on NNT and study flaws." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9, "brief_justification": "Response is factually accurate, logically sound, and provides thorough, insightful analysis with clear structure and practical implications. Minor potential overstatement on p-value impossibility (actual p~0.68 is correct for these counts) but overall excellent." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "Response is factually accurate on ARR/NNT calculations, statistical implausibility, trial design flaws, and risk-benefit analysis. Thoroughly covers all four questions with clear structure, good explanations, and practical implications. Minor room for more depth on exact statistical tests but overall excellent." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.8, "brief_justification": "Accurate calculations and statistical critique; thorough explanations of biases, ethics, and approval considerations with clear structure." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.8, "brief_justification": "Accurate calculations and explanations with good statistical and methodological insights; covers all parts thoroughly and clearly." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.6, "brief_justification": "Response is factually accurate on key stats concepts and trial flaws, with thorough structured analysis, clear tables/formulas, and insightful critique beyond basics. Minor deduction as p-value approximation is roughly correct but not precisely 0.41, and power calc assumes specific parameters." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 8.8, "brief_justification": "The response accurately calculates ARR and NNT, correctly shows the p-value is not significant with the given sample, explains placebo control issues thoroughly with a table, and provides a balanced benefit-harm analysis with NNH. All parts are covered clearly and insightfully." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Accurate calculations and statistical critique; thorough analysis of biases and approval criteria with clear structure and practical implications." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.5, "brief_justification": "Accurate calculations and explanation for sample size, but answer cuts off before fully addressing placebo issue and side effects, reducing completeness and depth." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.55, "brief_justification": "Accurately computes ARR, NNT, and power analysis, explains biases and risk-benefit, but contains a minor error in LHH formula and some approximations." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "Accurate calculations and sound statistical reasoning; covers all questions with clear structure; offers solid analysis of design flaws and benefit-harm balance, though could include more detailed power calculations." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.25, "brief_justification": "Accurate calculations and clear explanations; covers all questions with reasonable depth and practical guidance, though could include more detailed power analysis." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 6.75, "brief_justification": "Calculations are correct, but the claim that 200 patients yields p<0.001 is inaccurate; significance analysis lacks proper power discussion. Answers cover all questions clearly, but depth on statistical adequacy is limited, affecting overall usefulness." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.65, "brief_justification": "Accurate calculations and logical critique; covers all questions thoroughly with clear structure and insightful analysis, offering practical guidance." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 8.45, "brief_justification": "Accurate calculations and solid critique of statistical claims and trial design; covers all questions clearly, though could add more on power analysis." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Accurate calculations and sound critique of statistical significance, clear explanation of placebo issues, thorough coverage of all questions, well-structured, and offers practical guidance for further research." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.1, "brief_justification": "The calculations and statistical analysis regarding the p-value are excellent and insightful. However, the response is incomplete as it cuts off mid-sentence in section 3 and fails to address section 4 entirely." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 10, "brief_justification": "The response is exceptional. It correctly identifies that the claimed p-value is mathematically impossible given the sample size, provides a rigorous power analysis, and uses the Likelihood of Being Helped or Harmed (LHH) metric to provide a definitive recommendation against approval." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 10, "brief_justification": "The response is exceptionally accurate and thorough. It correctly identifies that the p-value is statistically impossible given the sample size and effect size, provides the correct ARR and NNT calculations, and offers a sophisticated analysis of the ethical and clinical considerations for drug approval." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 9.8, "brief_justification": "The response is exceptionally accurate and thorough. It correctly identifies that the reported p-value is mathematically impossible for the given sample size and proportions using standard tests. The calculations for ARR and NNT are correct, and the analysis of the lack of placebo and the risk-benefit ratio for approval is nuanced and professional." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 9.55, "brief_justification": "The response is excellent. It correctly calculates ARR and NNT, provides a nuanced analysis of the statistical significance (noting the low event count despite the p-value), explains the biases inherent in non-placebo trials, and offers a logical risk-benefit analysis regarding approval." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 10, "brief_justification": "The response is exceptional. It correctly identifies that the p-value claim is mathematically impossible for the given sample size, provides a rigorous power analysis, correctly calculates NNT and NNH, and offers a sophisticated critique of the trial design and ethical implications." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 10, "brief_justification": "The response is exceptionally accurate and insightful. It correctly identifies that the reported p-value is statistically impossible given the sample size and event rates, providing a clear mathematical demonstration. It also provides a nuanced critique of the trial design and the risk-benefit ratio." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 10, "brief_justification": "The response is exceptionally accurate and thorough. It correctly identifies that a p-value of <0.001 is mathematically impossible with the provided sample size and event rates, providing the statistical proof. The calculation of ARR, NNT, and NNH is perfect, and the qualitative analysis of the trial design flaws is comprehensive." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.9, "brief_justification": "Correctly calculates ARR (2%) and NNT (50). Makes a valid point about the suspiciously low p-value with small sample size. However, the response is incomplete - it cuts off mid-sentence and fails to address question 4 about whether the drug should be approved given the 8% side effects. The analysis stops before providing a benefit-risk assessment." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.75, "brief_justification": "Accurate calculations for ARR (2%) and NNT (50), thorough power analysis showing ~25x underpowered study, comprehensive bias discussion, and clear risk-benefit conclusion. Slight deduction for strong accusation of data fabrication beyond what the data strictly supports. Excellent depth and practical utility." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9, "brief_justification": "Thorough and accurate response covering all parts of the question with clear calculations, appropriate statistical skepticism, and nuanced benefit-harm analysis." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 7.9, "brief_justification": "Accurate on ARR/NNT calculations and provides good explanations for placebo issues and risk-benefit analysis. However, contains a significant statistical error in part 2 - the z-score calculation yields p ≈ 0.41, not 0.20 as claimed, though the conclusion that 200 patients is insufficient for p < 0.001 is still correct." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 7.35, "brief_justification": "Correctly calculates ARR (2%) and NNT (50). Part 2 is somewhat generous in concluding 200 patients is sufficient - with only 6 total events, there are legitimate concerns about reliability. Part 3 provides good explanation of bias issues. Part 4 gives balanced analysis of NNT vs NNH. Well-structured and clear, though could benefit from deeper discussion of power calculations and more regulatory considerations." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.75, "brief_justification": "Accurate calculations for ARR, NNT, and NNH. Correctly identifies sample size inadequacy and questions the p-value claim. Comprehensive analysis of no-treatment control issues. Well-structured with tables and equations. Provides nuanced benefit-risk analysis with conditional recommendations. Minor扣分: power calculation uses p<0.001 instead of p<0.05, and assumes equal group allocation not specified." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9, "brief_justification": "Accurate calculations (ARR 2%, NNT 50), correct identification that p<0.001 is statistically impossible with n=200, thorough explanation of control group design flaws, and clear recommendation against approval. Well-structured with strong depth on statistical reasoning and bias concepts." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.8, "brief_justification": "Accurate calculations (ARR=2%, NNT=50, NNH≈13) with correct statistical analysis showing p≈0.4-0.7 contradicts reported p<0.001. Thorough coverage including methodological issues, benefit-risk analysis, and regulatory considerations. Clear structure with tables and formulas. Good depth with multiple valid points on placebo control issues and quantitative benefit-harm comparison. Highly practical with actionable recommendations for larger trials and specific sample size suggestions (2,000-3,000 p" }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.45, "brief_justification": "Accurate calculations (ARR=2%, NNT=50) and correct statistical analysis showing p≈0.68 contradicts claimed p<0.001. Thorough explanation of placebo problems and benefit/harm ratio (8% side effects vs 2% benefit). Well-structured with clear headings and actionable conclusion recommending against approval pending Phase III trials." } ], "meta": { "source": "The Multivac (app.themultivac.com)", "methodology": "10x10 blind peer matrix evaluation", "criteria": "correctness, completeness, clarity, depth, usefulness", "self_judgments": "excluded from rankings", "license": "Open data — cite as: The Multivac (2026)" } }