{"id":"W7161853630","doi":"10.82308/43192","title":"A weighted casebase framework for predicting risk in survival data","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Covariate; Proportional hazards model; Parametric statistics; Sampling (signal processing); Logistic regression; Hazard; Regression; Function (biology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.03975073,0.001562599,0.001846359,0.004776147,0.0008380537,0.003337048,0.005052603,0.001860821,0.007173193],"category_scores_gemma":[0.1030593,0.001326068,0.002892263,0.004594075,0.001496973,0.00455673,0.003130547,0.003761663,0.002132686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001934506,"about_ca_system_score_gemma":0.00287085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007565138,"about_ca_topic_score_gemma":0.005982856,"domain_scores_codex":[0.9754734,0.01725632,0.001206859,0.002986122,0.002657939,0.0004193604],"domain_scores_gemma":[0.9432533,0.04507302,0.003240207,0.004837988,0.003089263,0.0005061682],"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":[0.0003016995,0.000241532,0.01257775,0.0006491941,0.0007869052,0.0006565651,0.000610118,0.2456389,0.0009476729,0.4351027,0.01303681,0.2894502],"study_design_scores_gemma":[0.00007559874,0.0001575636,0.001633034,0.0001837913,0.0001715809,0.0003714577,0.0001165756,0.5816681,0.0005454131,0.3951229,0.01989257,0.00006142226],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001681504,0.0003511157,0.9960819,0.0003287689,0.00005526277,0.000173411,0.0005467155,0.0002318587,0.0005495372],"genre_scores_gemma":[0.08614565,0.001648041,0.903527,0.0004382815,0.0002792156,0.001927337,0.002979264,0.0002292078,0.002825975],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03975073,"threshold_uncertainty_score":0.2102244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.20606206187163,"score_gpt":0.47148764065212,"score_spread":0.2654255787804899,"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."}}