{"id":"W6930246026","doi":"10.5281/zenodo.10649028","title":"SEAO datasets - raw and cleaned datasets","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Raw data; Key (lock); Deep learning; Calibration; Big data","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001167456,0.00206114,0.001124585,0.003386088,0.001635844,0.001847011,0.003445763,0.001754608,0.01551353],"category_scores_gemma":[0.004371726,0.0004586238,0.001396261,0.006042497,0.0007922495,0.0006545375,0.001519456,0.001739591,0.01719081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00711578,"about_ca_system_score_gemma":0.01055063,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7084672,"about_ca_topic_score_gemma":0.8550003,"domain_scores_codex":[0.9989296,0.0001318413,0.00007951789,0.0002129296,0.0003912694,0.0002548147],"domain_scores_gemma":[0.9976779,0.0002488417,0.0001134682,0.0004214779,0.001259547,0.0002789354],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001005016,0.00008005057,0.003309968,0.0003284794,0.00008119928,0.00007597395,0.00003823042,0.00174216,0.0001848627,0.0007931251,0.9883033,0.004962207],"study_design_scores_gemma":[0.000311743,0.00003703899,0.02776056,0.0003648681,0.00007216249,0.0001657174,0.0003407238,0.004818676,0.000829623,0.002005919,0.9631991,0.00009386101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001546646,0.0001849645,0.0002020924,0.0001259891,0.00004240097,0.00004411775,0.9959722,0.0005739918,0.001307601],"genre_scores_gemma":[0.001624935,0.00007341551,0.0005110745,0.00003729259,0.000006289351,0.00005358382,0.9968156,0.00005526557,0.0008225057],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7084672,"threshold_uncertainty_score":0.5864993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02835929016701918,"score_gpt":0.2818292272045106,"score_spread":0.2534699370374915,"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."}}