{"id":"W3019617362","doi":"10.1002/sim.8508","title":"A multiparameter regression model for interval‐censored survival data","year":2020,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Irish Research Council","keywords":"Proportional hazards model; Statistics; Interval (graph theory); Weibull distribution; Survival analysis; Computer science; Regression; Parametric statistics; Accelerated failure time model; Confidence interval; Regression analysis; Parametric model; Longitudinal data; Econometrics; Mathematics; Data mining","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":[0.01451366,0.001276364,0.001691324,0.00164969,0.0003708547,0.001701531,0.003620123,0.002044503,0.00389971],"category_scores_gemma":[0.03248673,0.0006496735,0.002433913,0.002488993,0.001198382,0.002371934,0.001591186,0.004007393,0.001150781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041902,"about_ca_system_score_gemma":0.001410917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002713262,"about_ca_topic_score_gemma":0.001673682,"domain_scores_codex":[0.9938989,0.00399899,0.000276618,0.000761381,0.0007722949,0.0002917953],"domain_scores_gemma":[0.9849893,0.01093504,0.001768395,0.00140936,0.0006612113,0.000236791],"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":[0.0001276032,0.00007593783,0.003330229,0.0003446417,0.0002318531,0.0004338884,0.0003213453,0.6409732,0.001837564,0.2729715,0.003740637,0.07561164],"study_design_scores_gemma":[0.00004985662,0.0001501389,0.0009778331,0.00008971872,0.00007141066,0.0002899945,0.00003051982,0.8744789,0.0003712061,0.1182631,0.005159835,0.00006751862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0042723,0.0004813289,0.993578,0.000580003,0.00003577006,0.00005816184,0.0002692862,0.000157018,0.0005680946],"genre_scores_gemma":[0.4347225,0.00391281,0.5457262,0.001013929,0.000396854,0.001679997,0.002126909,0.0003575505,0.01006318],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01451366,"threshold_uncertainty_score":0.07675648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4007317872209125,"score_gpt":0.4997713322034426,"score_spread":0.09903954498253009,"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."}}