{"id":"W2009397745","doi":"10.1002/cjs.5550340207","title":"Interval estimation via tail functions","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Confidence interval; Credible interval; Inference; Bernoulli's principle; Function (biology); Interval estimation; Mathematics; Coverage probability; Statistics; Interval (graph theory); Bayesian probability; Cutoff; Confidence distribution; Algorithm; Confidence region; Point estimation; Bayesian inference; Computer science; Artificial intelligence; Combinatorics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003317861,0.0001100213,0.0002294726,0.0001864309,0.0001259428,0.00007662814,0.0001331452,0.00005742275,0.0007490518],"category_scores_gemma":[0.001558987,0.0001000107,0.00004779507,0.0001398589,0.0001195662,0.000091054,0.00000540497,0.00021699,0.00003159998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001395927,"about_ca_system_score_gemma":0.000526737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002218961,"about_ca_topic_score_gemma":0.01129079,"domain_scores_codex":[0.99889,0.00007516755,0.0005442328,0.00008025177,0.0001723421,0.0002380087],"domain_scores_gemma":[0.9981974,0.0006955099,0.0002807238,0.0001156809,0.0003814441,0.0003292265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006966829,0.00002352211,0.0008805625,0.00004135038,0.00002297224,0.0001988536,0.00007946604,0.00003017444,0.00003296514,0.8233891,0.08880349,0.08649065],"study_design_scores_gemma":[0.0002020026,0.000126662,0.004138883,0.00005861009,0.00007994106,0.0001915482,0.00004769345,0.004650021,0.00003644998,0.9870951,0.003252499,0.0001206591],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0009837653,0.00003750604,0.9957603,0.0001793334,0.0005428485,0.00005408077,0.0004085957,0.000006951961,0.002026648],"genre_scores_gemma":[0.1579222,0.000001103138,0.8415526,0.00004633165,0.0001741591,0.000001178195,0.00001077945,0.00001517377,0.0002764028],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.163706,"threshold_uncertainty_score":0.8201592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03901419283689792,"score_gpt":0.3077683457835654,"score_spread":0.2687541529466675,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}