{"id":"W2081140142","doi":"10.1016/j.jmva.2008.04.014","title":"Order restricted inference for sequential k-out-of-n systems","year":2008,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":61,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Estimator; Inference; Sequential estimation; Extension (predicate logic); Maximum likelihood; Order statistic; Statistics; Sequential analysis; Applied mathematics; Order (exchange); Sample (material); Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01620696,0.001703369,0.006733693,0.001962662,0.001626471,0.00344708,0.004707968,0.003182201,0.005514755],"category_scores_gemma":[0.06954378,0.002748305,0.00307373,0.00181505,0.004059519,0.006432505,0.003420335,0.004344481,0.0007860921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001931003,"about_ca_system_score_gemma":0.003201381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01059743,"about_ca_topic_score_gemma":0.01405381,"domain_scores_codex":[0.9910787,0.003460987,0.0007549164,0.002764514,0.0009951212,0.0009457212],"domain_scores_gemma":[0.8711157,0.1125458,0.004779628,0.007244973,0.003147521,0.001166404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001133539,0.0003763554,0.008940103,0.0005410602,0.0008756076,0.0005785818,0.0005402857,0.8078398,0.001940103,0.1340792,0.001517734,0.04163749],"study_design_scores_gemma":[0.00005219584,0.00004697377,0.0006787181,0.00001289529,0.00005578789,0.00004947263,0.00002816436,0.9330597,0.0004151309,0.06536083,0.0002112575,0.00002893818],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04144305,0.0002972684,0.9562857,0.00033705,0.00006711762,0.00007838064,0.0002564109,0.0003131923,0.0009218711],"genre_scores_gemma":[0.8648925,0.000638114,0.126196,0.0003277409,0.0003469279,0.0003124836,0.001235157,0.0002137471,0.005837264],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01620696,"threshold_uncertainty_score":0.08571166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376170145518623,"score_gpt":0.4153484063940003,"score_spread":0.277731391842138,"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."}}