{"id":"W2027737251","doi":"10.1016/j.csda.2012.03.025","title":"Hybrid censoring: Models, inferential results and applications","year":2012,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":243,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Censoring (clinical trials); Computer science; Econometrics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003987366,0.0001750344,0.0002822285,0.0001791527,0.0003184748,0.0001102554,0.0002855443,0.0000404063,0.000179548],"category_scores_gemma":[0.0006098466,0.0001823214,0.00004554164,0.0005499266,0.0001353372,0.0003408678,0.000243994,0.0001234613,0.00007014196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004548177,"about_ca_system_score_gemma":0.00004854998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005962115,"about_ca_topic_score_gemma":0.00001712791,"domain_scores_codex":[0.9982025,0.000073585,0.0006073321,0.0004190457,0.0004207994,0.000276753],"domain_scores_gemma":[0.9970917,0.001429008,0.0002392779,0.0006709408,0.0002930332,0.0002760628],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008387531,0.0001927468,0.0003150938,0.0000269237,0.0003310219,4.840917e-7,0.00003564634,0.005420047,7.980886e-7,0.9748991,0.01380717,0.004962593],"study_design_scores_gemma":[0.0002379652,0.000004054006,0.01153826,0.000002913969,0.0009581582,0.000003416467,0.00001030792,0.5649009,0.000001359327,0.4182849,0.003902879,0.000154822],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003785285,0.00005849441,0.9468721,0.0001393036,0.00002622273,0.0002201625,0.05158101,0.00008674533,0.0006374615],"genre_scores_gemma":[0.558625,0.00003085487,0.3976021,0.00005553938,0.0001031059,0.00005220399,0.0434437,0.00001278922,0.00007479572],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5594809,"threshold_uncertainty_score":0.7434849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1773308485981085,"score_gpt":0.4040035739452627,"score_spread":0.2266727253471542,"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."}}