{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01388361,0.001169448,0.001590696,0.005434093,0.0005854496,0.003065947,0.002210979,0.002043139,0.004601704],"category_scores_gemma":[0.1058693,0.000809769,0.001513205,0.003281064,0.002228171,0.003894534,0.002936247,0.004520765,0.001540949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001212529,"about_ca_system_score_gemma":0.00111437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001829968,"about_ca_topic_score_gemma":0.0007355564,"domain_scores_codex":[0.9899153,0.006065272,0.00048645,0.0008547166,0.002348711,0.0003297119],"domain_scores_gemma":[0.9239796,0.06258769,0.002824137,0.005704211,0.00442323,0.0004810505],"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":[0.0003152729,0.00009236652,0.003917405,0.0004794685,0.0002956054,0.0002415716,0.0003916081,0.1633777,0.003772083,0.4955146,0.005352177,0.3262502],"study_design_scores_gemma":[0.00006562352,0.00007171584,0.001124588,0.0001730327,0.00007333515,0.0001908056,0.00003114753,0.696492,0.003317236,0.2921147,0.006266831,0.00007906924],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001355546,0.0003040163,0.9971685,0.00007953197,0.00003956431,0.00001598637,0.00003958106,0.0002746299,0.0007227663],"genre_scores_gemma":[0.2209884,0.001506975,0.7719043,0.0004773048,0.0003878707,0.0004573645,0.0005783796,0.0005109953,0.003188347],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01388361,"threshold_uncertainty_score":0.0734244,"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."}}