{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02449265,0.001665717,0.002944009,0.003462436,0.001185894,0.005254366,0.00456061,0.00273792,0.004951412],"category_scores_gemma":[0.09518831,0.001065507,0.002573468,0.00587312,0.00556043,0.00775192,0.003760742,0.004363308,0.000816814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001610722,"about_ca_system_score_gemma":0.001738523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002494675,"about_ca_topic_score_gemma":0.001591109,"domain_scores_codex":[0.988454,0.007578291,0.0004974816,0.00141044,0.001715932,0.000343851],"domain_scores_gemma":[0.8615634,0.117298,0.005209409,0.0122774,0.002882836,0.0007689627],"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":[0.0002197952,0.0001438997,0.009341232,0.00051594,0.0004684337,0.000397779,0.0006464077,0.06335473,0.0004724221,0.8211964,0.003505649,0.09973726],"study_design_scores_gemma":[0.00002838713,0.00003962328,0.0009239554,0.00007235895,0.00009599955,0.0001930724,0.00007334865,0.2026832,0.0002728702,0.794032,0.001557084,0.00002807624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005461384,0.001316022,0.9916286,0.0005383642,0.0000404846,0.00002535376,0.0001467252,0.0001272966,0.0007157638],"genre_scores_gemma":[0.4775438,0.006820964,0.5033977,0.0008824483,0.001019039,0.0006757318,0.00114342,0.0003613313,0.008155466],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02449265,"threshold_uncertainty_score":0.1295311,"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."}}