{"id":"W3208391743","doi":"10.5281/zenodo.3267531","title":"CamDavidsonPilon/lifelines: v0.22.0","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008070329,0.0001495756,0.0002140098,0.0001273063,0.000691131,0.0004349691,0.0007353035,0.00007146555,0.03287148],"category_scores_gemma":[0.003038411,0.0001400896,0.0000553899,0.0003709912,0.0001020015,0.0001490248,0.0005828561,0.000261291,0.01710246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007548836,"about_ca_system_score_gemma":0.000004057329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008272001,"about_ca_topic_score_gemma":9.905475e-8,"domain_scores_codex":[0.9982247,0.000353309,0.0003020239,0.000379365,0.0003781458,0.00036245],"domain_scores_gemma":[0.9984887,0.000213717,0.0001030493,0.0005382127,0.0004813668,0.0001749408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006322625,0.0001885336,0.00002380605,0.0002168236,0.00004304454,0.00001602991,0.0005985118,0.000001833622,0.002964226,0.5494437,0.2491453,0.197295],"study_design_scores_gemma":[0.0005063207,0.0002668017,0.0002917839,0.00006152086,0.00001956538,0.00007376483,0.0002293637,0.0005633203,0.0004286619,0.1150611,0.8822441,0.0002537668],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02367641,0.0000470046,0.5809178,0.001031528,0.000397919,0.000944916,0.0003785623,0.00152848,0.3910774],"genre_scores_gemma":[0.668204,0.00007826134,0.3139094,0.0007623139,0.001106266,1.743275e-7,0.0008901893,0.004756874,0.01029247],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6445276,"threshold_uncertainty_score":0.9836628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07594689455677812,"score_gpt":0.3332292661522704,"score_spread":0.2572823715954923,"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."}}