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| # Statistics report | |
| ## Headline intervals: fastapi | |
| | config | metric | mean | 95 percent interval (primary) | naive SE | clustered SE | n_clusters | design effect | | |
| |---|---|---|---|---|---|---|---| | |
| | custom-anthropic+0bc9cd53 | p_at_5 | 0.791 | [0.664, 0.917] (clustered) | 0.0566 | 0.0645 | n_clusters=12 | design effect=1.30 | | |
| | custom-anthropic+0bc9cd53 | r_at_5 | 0.841 | [0.710, 0.971] (clustered) | 0.0662 | 0.0666 | n_clusters=12 | design effect=1.01 | | |
| | custom-openai+470d79fa | p_at_5 | 0.718 | [0.610, 0.827] (clustered) | 0.0667 | 0.0554 | n_clusters=12 | design effect=0.69 | | |
| | custom-openai+470d79fa | r_at_5 | 0.833 | [0.715, 0.951] (clustered) | 0.0719 | 0.0602 | n_clusters=12 | design effect=0.70 | | |
| | langchain-anthropic+claude-haiku-4-5-20251001 | p_at_5 | 0.760 | [0.645, 0.875] (clustered) | 0.0606 | 0.0589 | n_clusters=12 | design effect=0.94 | | |
| | langchain-anthropic+claude-haiku-4-5-20251001 | r_at_5 | 0.841 | [0.710, 0.971] (clustered) | 0.0662 | 0.0666 | n_clusters=12 | design effect=1.01 | | |
| | langchain-openai+gpt-4o-mini | p_at_5 | 0.627 | [0.484, 0.770] (clustered) | 0.0683 | 0.0729 | n_clusters=12 | design effect=1.14 | | |
| | langchain-openai+gpt-4o-mini | r_at_5 | 0.836 | [0.702, 0.971] (clustered) | 0.0716 | 0.0685 | n_clusters=12 | design effect=0.91 | | |
| ## Citation accuracy zero-failure bound: fastapi | |
| - custom-anthropic+0bc9cd53: 0 failures in 21 included questions (included n=21, excluded 1 citation-free questions; cited in all epochs: 21, in some epochs: 0). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.133 (rule of three approximation 3/n = 0.143). | |
| - custom-openai+470d79fa: 0 failures in 19 included questions (included n=19, excluded 3 citation-free questions; cited in all epochs: 19, in some epochs: 0). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.146 (rule of three approximation 3/n = 0.158). | |
| - langchain-anthropic+claude-haiku-4-5-20251001: 0 failures in 20 included questions (included n=20, excluded 2 citation-free questions; cited in all epochs: 20, in some epochs: 0). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.139 (rule of three approximation 3/n = 0.150). | |
| - langchain-openai+gpt-4o-mini: 0 failures in 20 included questions (included n=20, excluded 2 citation-free questions; cited in all epochs: 19, in some epochs: 1). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.139 (rule of three approximation 3/n = 0.150). | |
| ## Framework equivalence (TOST): fastapi | |
| - custom-anthropic+0bc9cd53 vs langchain-anthropic+claude-haiku-4-5-20251001, p_at_5: mean diff +0.031, 90 percent CI [-0.013, +0.076], n=12: equivalent within plus or minus 0.10; the data support equivalence down to plus or minus 0.076. | |
| - custom-anthropic+0bc9cd53 vs langchain-anthropic+claude-haiku-4-5-20251001, r_at_5: mean diff +0.000, 90 percent CI [+0.000, +0.000], n=12: equivalent within plus or minus 0.10; the data support equivalence down to plus or minus 0.000. | |
| - custom-anthropic+0bc9cd53 vs langchain-openai+gpt-4o-mini, p_at_5: mean diff +0.164, 90 percent CI [+0.031, +0.317], n=12: equivalence not established at plus or minus 0.10; the data support only plus or minus 0.317. | |
| - custom-anthropic+0bc9cd53 vs langchain-openai+gpt-4o-mini, r_at_5: mean diff +0.005, 90 percent CI [-0.076, +0.095], n=12: equivalent within plus or minus 0.10; the data support equivalence down to plus or minus 0.095. | |
| - custom-openai+470d79fa vs langchain-anthropic+claude-haiku-4-5-20251001, p_at_5: mean diff -0.042, 90 percent CI [-0.105, +0.016], n=12: equivalence not established at plus or minus 0.10; the data support only plus or minus 0.105. | |
| - custom-openai+470d79fa vs langchain-anthropic+claude-haiku-4-5-20251001, r_at_5: mean diff -0.008, 90 percent CI [-0.100, +0.068], n=12: equivalence not established at plus or minus 0.10; the data support only plus or minus 0.100. | |
| - custom-openai+470d79fa vs langchain-openai+gpt-4o-mini, p_at_5: mean diff +0.091, 90 percent CI [-0.010, +0.202], n=12: equivalence not established at plus or minus 0.10; the data support only plus or minus 0.202. | |
| - custom-openai+470d79fa vs langchain-openai+gpt-4o-mini, r_at_5: mean diff -0.003, 90 percent CI [-0.043, +0.032], n=12: equivalent within plus or minus 0.10; the data support equivalence down to plus or minus 0.043. | |
| ## Variance decomposition and power: fastapi | |
| - p_at_5 variance: between-question 0.06051, within-question 0.00036, ICC 0.99 (22 questions x 5 epochs). | |
| - Error budget preview: the interval above is the statistical term only; template sensitivity and judge bias are systematic terms, scoped for v3.2. | |
| - Minimum detectable p_at_5 difference at 80 percent power: 0.110 (normal approximation 0.136). | |
| ## Refusal reliability (pass^k): fastapi | |
| | config | k | single-run | pass^k | 95 percent interval | n_questions | | |
| |---|---|---|---|---|---| | |
| | custom-anthropic+0bc9cd53 | 5 | 0.560 | 0.400 | [0.053, 0.853] | 5 | | |
| | custom-openai+470d79fa | 5 | 0.640 | 0.600 | [0.147, 0.947] | 5 | | |
| | langchain-anthropic+claude-haiku-4-5-20251001 | 5 | 0.200 | 0.200 | [0.005, 0.716] | 5 | | |
| | langchain-openai+gpt-4o-mini | 5 | 0.760 | 0.600 | [0.147, 0.947] | 5 | | |
| ## Headline intervals: k8s | |
| | config | metric | mean | 95 percent interval (primary) | naive SE | clustered SE | n_clusters | design effect | | |
| |---|---|---|---|---|---|---|---| | |
| | custom-anthropic-k8s+0bc9cd53 | p_at_5 | 0.823 | [0.736, 0.910] (question-level) | 0.0444 | 0.0510 | n_clusters=6 | design effect=1.32 | | |
| | custom-anthropic-k8s+0bc9cd53 | r_at_5 | 0.943 | [0.881, 1.000] (question-level) | 0.0319 | 0.0537 | n_clusters=6 | design effect=2.82 | | |
| | custom-openai-k8s+470d79fa | p_at_5 | 0.814 | [0.734, 0.894] (question-level) | 0.0408 | 0.0504 | n_clusters=6 | design effect=1.53 | | |
| | custom-openai-k8s+470d79fa | r_at_5 | 0.957 | [0.898, 1.000] (question-level) | 0.0300 | 0.0413 | n_clusters=6 | design effect=1.89 | | |
| ceiling-censored: k8s custom-anthropic-k8s+0bc9cd53 r_at_5: the normal-approximation interval extends past the [0,1] proportion bound and is reported clamped to it; the bound sits on the ceiling rather than estimating beyond it. | |
| correlation-sensitivity caution: k8s custom-anthropic-k8s+0bc9cd53 r_at_5: clustered SE 0.0537 exceeds 1.5x the question-level SE 0.0319; the question-level headline interval likely understates uncertainty. | |
| ceiling-censored: k8s custom-openai-k8s+470d79fa r_at_5: the normal-approximation interval extends past the [0,1] proportion bound and is reported clamped to it; the bound sits on the ceiling rather than estimating beyond it. | |
| ## Citation accuracy zero-failure bound: k8s | |
| - custom-anthropic-k8s+0bc9cd53: 0 failures in 22 included questions (included n=22, excluded 1 citation-free questions; cited in all epochs: 20, in some epochs: 2). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.127 (rule of three approximation 3/n = 0.136). | |
| - custom-openai-k8s+470d79fa: 0 failures in 22 included questions (included n=22, excluded 1 citation-free questions; cited in all epochs: 21, in some epochs: 1). Exact Clopper-Pearson 95 percent upper bound on the per-question failure rate: 0.127 (rule of three approximation 3/n = 0.136). | |
| ## Framework equivalence (TOST): k8s | |
| ## Variance decomposition and power: k8s | |
| - p_at_5 variance: between-question 0.03249, within-question 0.00209, ICC 0.94 (23 questions x 5 epochs). | |
| - Error budget preview: the interval above is the statistical term only; template sensitivity and judge bias are systematic terms, scoped for v3.2. | |
| - Minimum detectable p_at_5 difference at 80 percent power: 0.119 (normal approximation 0.110). | |
| ## Refusal reliability (pass^k): k8s | |
| | config | k | single-run | pass^k | 95 percent interval | n_questions | | |
| |---|---|---|---|---|---| | |
| | custom-anthropic-k8s+0bc9cd53 | 5 | 0.800 | 0.500 | [0.013, 0.987] | 2 | | |
| | custom-openai-k8s+470d79fa | 5 | 1.000 | 1.000 | [0.158, 1.000] | 2 | | |
| ## Methods appendix | |
| - Estimators: cluster bootstrap over cluster_id (10000 replicates); paired bootstrap on per-question epoch-mean differences; TOST at margin 0.10 absolute, alpha 0.05 per one-sided test, no multiplicity adjustment across P@5 and R@5 (pre-registered, design spec section 2, frozen 2026-06-11 before any WP5 data existed). | |
| - Zero-failure bounding: a question succeeds only if zero hallucinated citations occurred across all epochs and all citations; collapsing epochs bounds the any-of-k failure rate, which also bounds the per-answer rate. | |
| - Seed: 20260611. No wall-clock values appear in this report. | |
| - Input table fastapi: 1878 rows, content hash c28484520117. | |
| - Input table k8s: 925 rows, content hash 986cda71bb39. | |
| ## README values | |
| - fastapi_custom_anthropic_p_at_5_mean = 0.791 | |
| - fastapi_custom_anthropic_p_at_5_ci = [0.664, 0.917] | |
| - fastapi_custom_anthropic_r_at_5_mean = 0.841 | |
| - fastapi_custom_anthropic_r_at_5_ci = [0.710, 0.971] | |
| - fastapi_custom_openai_p_at_5_mean = 0.718 | |
| - fastapi_custom_openai_p_at_5_ci = [0.610, 0.827] | |
| - fastapi_custom_openai_r_at_5_mean = 0.833 | |
| - fastapi_custom_openai_r_at_5_ci = [0.715, 0.951] | |
| - fastapi_langchain_anthropic_p_at_5_mean = 0.760 | |
| - fastapi_langchain_anthropic_p_at_5_ci = [0.645, 0.875] | |
| - fastapi_langchain_anthropic_r_at_5_mean = 0.841 | |
| - fastapi_langchain_anthropic_r_at_5_ci = [0.710, 0.971] | |
| - fastapi_langchain_openai_p_at_5_mean = 0.627 | |
| - fastapi_langchain_openai_p_at_5_ci = [0.484, 0.770] | |
| - fastapi_langchain_openai_r_at_5_mean = 0.836 | |
| - fastapi_langchain_openai_r_at_5_ci = [0.702, 0.971] | |
| - fastapi_custom_anthropic_citation_n = 21 | |
| - fastapi_custom_anthropic_citation_upper = 0.133 | |
| - fastapi_custom_anthropic_citation_rule_of_three = 0.143 | |
| - fastapi_custom_openai_citation_n = 19 | |
| - fastapi_custom_openai_citation_upper = 0.146 | |
| - fastapi_custom_openai_citation_rule_of_three = 0.158 | |
| - fastapi_langchain_anthropic_citation_n = 20 | |
| - fastapi_langchain_anthropic_citation_upper = 0.139 | |
| - fastapi_langchain_anthropic_citation_rule_of_three = 0.150 | |
| - fastapi_langchain_openai_citation_n = 20 | |
| - fastapi_langchain_openai_citation_upper = 0.139 | |
| - fastapi_langchain_openai_citation_rule_of_three = 0.150 | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_p_at_5_tost = equivalent | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_p_at_5_support = 0.076 | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_p_at_5_diff = +0.031 | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_p_at_5_ci90 = [-0.013, +0.076] | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_p_at_5_ci95 = [-0.021, +0.086] | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_r_at_5_tost = equivalent | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_r_at_5_support = 0.000 | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_r_at_5_diff = +0.000 | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_r_at_5_ci90 = [+0.000, +0.000] | |
| - fastapi_custom_anthropic_vs_langchain_anthropic_r_at_5_ci95 = [+0.000, +0.000] | |
| - fastapi_custom_anthropic_vs_langchain_openai_p_at_5_tost = not established | |
| - fastapi_custom_anthropic_vs_langchain_openai_p_at_5_support = 0.317 | |
| - fastapi_custom_anthropic_vs_langchain_openai_p_at_5_diff = +0.164 | |
| - fastapi_custom_anthropic_vs_langchain_openai_p_at_5_ci90 = [+0.031, +0.317] | |
| - fastapi_custom_anthropic_vs_langchain_openai_p_at_5_ci95 = [+0.016, +0.353] | |
| - fastapi_custom_anthropic_vs_langchain_openai_r_at_5_tost = equivalent | |
| - fastapi_custom_anthropic_vs_langchain_openai_r_at_5_support = 0.095 | |
| - fastapi_custom_anthropic_vs_langchain_openai_r_at_5_diff = +0.005 | |
| - fastapi_custom_anthropic_vs_langchain_openai_r_at_5_ci90 = [-0.076, +0.095] | |
| - fastapi_custom_anthropic_vs_langchain_openai_r_at_5_ci95 = [-0.086, +0.111] | |
| - fastapi_custom_openai_vs_langchain_anthropic_p_at_5_tost = not established | |
| - fastapi_custom_openai_vs_langchain_anthropic_p_at_5_support = 0.105 | |
| - fastapi_custom_openai_vs_langchain_anthropic_p_at_5_diff = -0.042 | |
| - fastapi_custom_openai_vs_langchain_anthropic_p_at_5_ci90 = [-0.105, +0.016] | |
| - fastapi_custom_openai_vs_langchain_anthropic_p_at_5_ci95 = [-0.118, +0.023] | |
| - fastapi_custom_openai_vs_langchain_anthropic_r_at_5_tost = not established | |
| - fastapi_custom_openai_vs_langchain_anthropic_r_at_5_support = 0.100 | |
| - fastapi_custom_openai_vs_langchain_anthropic_r_at_5_diff = -0.008 | |
| - fastapi_custom_openai_vs_langchain_anthropic_r_at_5_ci90 = [-0.100, +0.068] | |
| - fastapi_custom_openai_vs_langchain_anthropic_r_at_5_ci95 = [-0.114, +0.076] | |
| - fastapi_custom_openai_vs_langchain_openai_p_at_5_tost = not established | |
| - fastapi_custom_openai_vs_langchain_openai_p_at_5_support = 0.202 | |
| - fastapi_custom_openai_vs_langchain_openai_p_at_5_diff = +0.091 | |
| - fastapi_custom_openai_vs_langchain_openai_p_at_5_ci90 = [-0.010, +0.202] | |
| - fastapi_custom_openai_vs_langchain_openai_p_at_5_ci95 = [-0.026, +0.227] | |
| - fastapi_custom_openai_vs_langchain_openai_r_at_5_tost = equivalent | |
| - fastapi_custom_openai_vs_langchain_openai_r_at_5_support = 0.043 | |
| - fastapi_custom_openai_vs_langchain_openai_r_at_5_diff = -0.003 | |
| - fastapi_custom_openai_vs_langchain_openai_r_at_5_ci90 = [-0.043, +0.032] | |
| - fastapi_custom_openai_vs_langchain_openai_r_at_5_ci95 = [-0.055, +0.040] | |
| - fastapi_significant_pairs_95 = custom_anthropic vs langchain_openai p_at_5 | |
| - fastapi_significant_pairs_95_count = 1 | |
| - fastapi_icc_p_at_5 = 0.99 | |
| - fastapi_between_question_var_p_at_5 = 0.06051 | |
| - fastapi_within_question_var_p_at_5 = 0.00036 | |
| - fastapi_within_question_pct = 0.6 | |
| - fastapi_mde_p_at_5_80 = 0.110 | |
| - fastapi_mde_p_at_5_80_normal = 0.136 | |
| - k8s_custom_anthropic_k8s_p_at_5_mean = 0.823 | |
| - k8s_custom_anthropic_k8s_p_at_5_ci = [0.736, 0.910] | |
| - k8s_custom_anthropic_k8s_r_at_5_mean = 0.943 | |
| - k8s_custom_anthropic_k8s_r_at_5_ci = [0.881, 1.000] | |
| - k8s_custom_openai_k8s_p_at_5_mean = 0.814 | |
| - k8s_custom_openai_k8s_p_at_5_ci = [0.734, 0.894] | |
| - k8s_custom_openai_k8s_r_at_5_mean = 0.957 | |
| - k8s_custom_openai_k8s_r_at_5_ci = [0.898, 1.000] | |
| - k8s_custom_anthropic_k8s_citation_n = 22 | |
| - k8s_custom_anthropic_k8s_citation_upper = 0.127 | |
| - k8s_custom_anthropic_k8s_citation_rule_of_three = 0.136 | |
| - k8s_custom_openai_k8s_citation_n = 22 | |
| - k8s_custom_openai_k8s_citation_upper = 0.127 | |
| - k8s_custom_openai_k8s_citation_rule_of_three = 0.136 | |
| - k8s_significant_pairs_95 = none | |
| - k8s_significant_pairs_95_count = 0 | |
| - k8s_icc_p_at_5 = 0.94 | |
| - k8s_between_question_var_p_at_5 = 0.03249 | |
| - k8s_within_question_var_p_at_5 = 0.00209 | |
| - k8s_within_question_pct = 6.0 | |
| - k8s_mde_p_at_5_80 = 0.119 | |
| - k8s_mde_p_at_5_80_normal = 0.110 | |