{"id":"W6958221247","doi":"10.6084/m9.figshare.21629034","title":"Additional file 1 of Effective hospital readmission prediction models using machine-learned features","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Predictive modelling; Hospital readmission; MEDLINE; Logistic regression","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001262665,0.001144085,0.0008680405,0.001599862,0.0004133742,0.001193358,0.001762334,0.001409523,0.853976],"category_scores_gemma":[0.03005953,0.0005507082,0.0009622992,0.001590927,0.00019428,0.001303625,0.0007126188,0.001008832,0.2001155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007153967,"about_ca_system_score_gemma":0.001287839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004680791,"about_ca_topic_score_gemma":0.008892523,"domain_scores_codex":[0.9995745,0.00009978218,0.00006813625,0.0001200919,0.00008433828,0.00005316161],"domain_scores_gemma":[0.9766954,0.01963422,0.0005912701,0.0009618244,0.001848303,0.0002689832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004784646,0.0002792442,0.003258986,0.002029169,0.00009463531,0.00007192132,0.00002933433,0.002824401,0.0001332748,0.0008396502,0.9649577,0.02500315],"study_design_scores_gemma":[0.01346113,0.001488907,0.05251544,0.004644652,0.0008215505,0.001145681,0.0004718454,0.07934628,0.004379673,0.05182205,0.789484,0.0004186934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0005036807,0.00003182407,0.0009030486,0.0001124659,0.00004819385,0.00007870894,0.9969291,0.0003797949,0.001013204],"genre_scores_gemma":[0.0208992,0.0001498246,0.01230527,0.0006140348,0.0001737558,0.001661625,0.9525884,0.0007896481,0.0108182],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.853976,"threshold_uncertainty_score":0.2082855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02976544707043605,"score_gpt":0.3071320909038595,"score_spread":0.2773666438334235,"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."}}