{"id":"W4385064319","doi":"10.1177/0272989x231188027","title":"Constrained Optimization for Decision Making in Health Care Using Python: A Tutorial","year":2023,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Childhood Cancer Survivors' Quality of Life","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Michael's Hospital; Queen's University; University of Toronto","funders":"","keywords":"Python (programming language); Computer science; Solver; Optimization problem; Mathematical optimization; Software; Programming language; Algorithm; Mathematics","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":[0.001756134,0.002025979,0.001107595,0.0008793825,0.0005952332,0.002371603,0.002160918,0.001599696,0.09225233],"category_scores_gemma":[0.00785768,0.001146928,0.002051449,0.001676629,0.0008858492,0.003820235,0.002379471,0.005349373,0.03130107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001078505,"about_ca_system_score_gemma":0.002488622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001910686,"about_ca_topic_score_gemma":0.002863577,"domain_scores_codex":[0.9990959,0.0003013666,0.00010513,0.0001225766,0.0002932353,0.00008175733],"domain_scores_gemma":[0.9967348,0.002534072,0.0001107309,0.0001461081,0.0003557587,0.0001185268],"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":[0.00008158523,0.0001898049,0.0005127561,0.003511103,0.00007733341,0.0005950434,0.0006954607,0.02699099,0.003039948,0.2196084,0.420944,0.3237536],"study_design_scores_gemma":[0.00006006745,0.0000380757,0.0005210906,0.0009901498,0.00002145719,0.0004946768,0.00008012526,0.04945338,0.001735233,0.176551,0.7699726,0.00008211711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008016194,0.004236028,0.9330298,0.003246601,0.0008524898,0.0004483264,0.00420189,0.01943098,0.03375234],"genre_scores_gemma":[0.01088352,0.01373952,0.9145007,0.004599198,0.001065183,0.002337602,0.005153744,0.01186996,0.0358506],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.09225233,"threshold_uncertainty_score":0.3086148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06140506149519503,"score_gpt":0.4364930278491112,"score_spread":0.3750879663539162,"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."}}