{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007486913,0.0001068602,0.0002655095,0.0001110713,0.0001000587,0.000004471441,0.0003170619,0.00002007077,0.0004248616],"category_scores_gemma":[0.000003883883,0.00009719117,0.00005544299,0.0002268009,0.00006435849,0.00005734078,0.0006213642,0.0001374596,0.00002672613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006719752,"about_ca_system_score_gemma":0.0000869713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007822773,"about_ca_topic_score_gemma":0.000008617042,"domain_scores_codex":[0.9989046,0.00004486816,0.0002578439,0.0002551658,0.0003958619,0.0001416527],"domain_scores_gemma":[0.9990239,0.00001425955,0.00007600384,0.000773124,0.0000167682,0.00009592678],"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":[0.00345614,0.008925575,0.2680909,0.0005919813,0.005898584,0.001230304,0.006876782,0.00004608919,0.04292117,0.002272992,0.5846734,0.07501609],"study_design_scores_gemma":[0.003806778,0.005352622,0.3072497,0.00009716298,0.0009687836,0.0002143294,0.001665681,0.0006920734,0.00437884,0.001082474,0.6740391,0.0004524651],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955299,0.0004830092,0.00001678904,0.0003217343,0.0006478035,0.000332517,0.000188497,0.00004812709,0.002431656],"genre_scores_gemma":[0.998028,0.0000478008,0.00006545018,0.0005486695,0.0000493351,0.00004941268,0.0008993096,0.00001463926,0.0002973771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08936564,"threshold_uncertainty_score":0.4651937,"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."}}