{"id":"W2470017617","doi":"10.1017/cem.2016.293","title":"P118: The utility of serum markers for diagnosing septic arthritis in the emergency department: do rigid cut-offs improve diagnostic characteristics?","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Hematological disorders and diagnostics","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Septic arthritis; Erythrocyte sedimentation rate; Emergency department; Arthritis; Cohort; Retrospective cohort study; C-reactive protein; White blood cell; Internal medicine; Gram staining; Inflammatory arthritis; Emergency medicine; Intensive care medicine; Surgery; Antibiotics; Inflammation","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":[0.01334748,0.001751027,0.00222796,0.003065786,0.0009661208,0.003087714,0.002079109,0.002426613,0.003053434],"category_scores_gemma":[0.09187549,0.0005525476,0.001574586,0.002453509,0.00125306,0.002642852,0.001357811,0.004280319,0.002005435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007776034,"about_ca_system_score_gemma":0.001259445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002049727,"about_ca_topic_score_gemma":0.002560887,"domain_scores_codex":[0.9918024,0.002987756,0.00166306,0.0006333671,0.00233364,0.0005798036],"domain_scores_gemma":[0.9418792,0.03272613,0.009859259,0.002593695,0.01051695,0.002424752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003983113,0.0002809374,0.8863684,0.0005284548,0.0005103173,0.0007399922,0.0002852894,0.0005357631,0.002099612,0.000736393,0.01005638,0.09387536],"study_design_scores_gemma":[0.0008958762,0.002689676,0.9445457,0.001943364,0.001460439,0.006934831,0.001695693,0.01380478,0.0051456,0.007463773,0.0132358,0.000184404],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9175978,0.0222208,0.009645572,0.02913312,0.002499858,0.0002835903,0.002377377,0.0002860054,0.01595583],"genre_scores_gemma":[0.9831349,0.002095355,0.008197623,0.002958596,0.001433535,0.00009537159,0.001496055,0.0000984158,0.0004902672],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01334748,"threshold_uncertainty_score":0.07058907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04927221874798263,"score_gpt":0.3191283184288515,"score_spread":0.2698560996808689,"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."}}