{"id":"W4213138050","doi":"10.1016/j.injury.2022.02.041","title":"Big data insights into predictors of acute compartment syndrome","year":2022,"lang":"en","type":"article","venue":"Injury","topic":"Muscle and Compartmental Disorders","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Office of the Under Secretary of Defense; U.S. Department of Defense","keywords":"Fasciotomy; Medicine; Cohort; Logistic regression; Retrospective cohort study; Culprit; Internal medicine; Surgery; Emergency medicine; Clinical trial; Myocardial infarction","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":[0.005462566,0.0009356474,0.001376858,0.004650766,0.0004899909,0.003932302,0.001349218,0.001199241,0.003918062],"category_scores_gemma":[0.04431105,0.0004827135,0.001282854,0.006753374,0.0005771206,0.00335944,0.002381823,0.003391707,0.0009343521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007138362,"about_ca_system_score_gemma":0.001799785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005647411,"about_ca_topic_score_gemma":0.008015645,"domain_scores_codex":[0.9959385,0.001557868,0.0006445036,0.0006544539,0.0008330758,0.0003715101],"domain_scores_gemma":[0.9475569,0.03279608,0.00879465,0.00425081,0.003967141,0.002634489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005396063,0.0001197087,0.906077,0.0007387222,0.001324611,0.0002853805,0.0003442192,0.003412448,0.0002575711,0.006468156,0.0284848,0.05194775],"study_design_scores_gemma":[0.0001053913,0.0002136591,0.8172723,0.002114882,0.001064953,0.0009483385,0.001919903,0.04846707,0.0008040672,0.08415651,0.0427533,0.0001796399],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.561185,0.07087146,0.03345621,0.09525625,0.003835456,0.0003427207,0.2114036,0.001421785,0.02222748],"genre_scores_gemma":[0.9039558,0.01415972,0.01409215,0.005470191,0.003006079,0.0002237222,0.05795184,0.000201488,0.000939126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005647411,"threshold_uncertainty_score":0.02888918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04004889274968586,"score_gpt":0.2965105654565517,"score_spread":0.2564616727068658,"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."}}