{"id":"W3016811362","doi":"10.2196/17648","title":"Toward Optimal Heparin Dosing by Comparing Multiple Machine Learning Methods: Retrospective Study","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Heparin-Induced Thrombocytopenia and Thrombosis","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dosing; Computer science; Medicine; Heparin; Retrospective cohort study; Machine learning; Artificial intelligence; Medical physics; Intensive care medicine; Surgery; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.008192492,0.0005373166,0.0007222538,0.001863206,0.0002458957,0.0007311744,0.0005477358,0.0006105155,0.0006899129],"category_scores_gemma":[0.02129498,0.0002912334,0.001036689,0.001062451,0.0003763778,0.000705089,0.0004346558,0.0005913047,0.0002958375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004038947,"about_ca_system_score_gemma":0.0004039468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001070983,"about_ca_topic_score_gemma":0.0007632606,"domain_scores_codex":[0.99527,0.002137275,0.0006355615,0.0009794523,0.0008418843,0.0001357873],"domain_scores_gemma":[0.9777891,0.01326098,0.003906554,0.002176611,0.002500849,0.0003659549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001471659,0.0002893985,0.9771398,0.00006088307,0.0004189793,0.0001200287,0.00010659,0.001633471,0.000276034,0.00008052953,0.0002988667,0.01810373],"study_design_scores_gemma":[0.0002999203,0.008826084,0.9225339,0.0001127192,0.001223985,0.002508248,0.0006808217,0.05753214,0.003099108,0.0004887669,0.002595724,0.00009862028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940596,0.0008097789,0.004151342,0.00003002018,0.00001466267,0.0000856169,0.0005339103,0.00001741072,0.0002976437],"genre_scores_gemma":[0.9962742,0.0002708443,0.00219721,0.00002666614,0.00002242894,0.00004999019,0.001072576,0.00001094313,0.0000751003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008192492,"threshold_uncertainty_score":0.04332656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07641253536434223,"score_gpt":0.3733224485144085,"score_spread":0.2969099131500663,"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."}}