{"id":"W3091343190","doi":"10.1016/j.jamcollsurg.2020.09.014","title":"Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?","year":2020,"lang":"en","type":"article","venue":"Journal of the American College of Surgeons","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Care Foundation","funders":"","keywords":"Amputation; Medicine; Logistic regression; Random forest; Machine learning; Surgery; Emergency medicine; Internal medicine; 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":[],"consensus_categories":[],"category_scores_codex":[0.0004519454,0.0001400694,0.0003738236,0.0000758623,0.0001068819,0.00002352076,0.000255431,0.00003342717,0.00002930771],"category_scores_gemma":[0.000478232,0.00008996193,0.0002355251,0.0006027292,0.0001241464,0.00006200139,0.00005252604,0.0003761703,8.648393e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009116027,"about_ca_system_score_gemma":0.00006731616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003421421,"about_ca_topic_score_gemma":0.00008186384,"domain_scores_codex":[0.9986146,0.0001896149,0.0005297706,0.00009126137,0.0003857732,0.000188991],"domain_scores_gemma":[0.9988556,0.0002748577,0.0004321485,0.0001322039,0.0001731834,0.000132043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001838076,0.0002630085,0.09424852,0.00009624751,0.0009159224,0.00005048096,0.01804411,0.8384401,0.02683544,0.00009420875,0.01237041,0.006803443],"study_design_scores_gemma":[0.005034802,0.003949172,0.6039306,0.0008513768,0.0009824762,0.0001015198,0.01359709,0.3287238,0.007744113,0.0004806968,0.03307503,0.001529281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882374,0.00003140999,0.001113314,0.009567267,0.0006505266,0.0001656818,0.0001711522,0.0000282047,0.00003500284],"genre_scores_gemma":[0.9991586,0.00001522493,0.0003252142,0.0003507453,0.00007486882,0.00000356919,0.000001415647,0.00003057077,0.00003979739],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5097163,"threshold_uncertainty_score":0.3668541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01198248515466389,"score_gpt":0.2219149883827148,"score_spread":0.2099325032280509,"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."}}