{"id":"W2588162329","doi":"10.1111/jvim.14670","title":"Prognostic Value and Development of a Scoring System in Horses With Systemic Inflammatory Response Syndrome","year":2017,"lang":"en","type":"article","venue":"Journal of Veterinary Internal Medicine","topic":"Veterinary Equine Medical Research","field":"Veterinary","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Alberta Innovates Bio Solutions; Natural Sciences and Engineering Research Council of Canada; Alberta Livestock and Meat Agency","keywords":"Medicine; Systemic inflammatory response syndrome; Inflammatory response; Systemic inflammation; Value (mathematics); Intensive care medicine; Internal medicine; Inflammation; Sepsis; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004973219,0.0007069713,0.0005020892,0.002046578,0.0002539985,0.000795995,0.0005161099,0.0005307295,0.0009971244],"category_scores_gemma":[0.01252624,0.0001697398,0.0004008091,0.0008608888,0.0004304395,0.0006883423,0.0006450149,0.0006336418,0.0002655521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002807105,"about_ca_system_score_gemma":0.0004877051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006609704,"about_ca_topic_score_gemma":0.0009054811,"domain_scores_codex":[0.9981987,0.00110153,0.0002093888,0.0001164493,0.0002543506,0.0001196242],"domain_scores_gemma":[0.9918069,0.003152579,0.003038932,0.0002305558,0.00117113,0.0005999558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001522025,0.00002734493,0.9960829,0.00001484591,0.00002201558,0.00003733885,0.00001963851,0.0001928211,0.0001671298,0.00001619017,0.0001199489,0.003147633],"study_design_scores_gemma":[0.00004559546,0.001276216,0.9810309,0.00006813753,0.000106423,0.0009343108,0.0002258361,0.01549976,0.000299049,0.000163721,0.0003319881,0.00001806498],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977494,0.0004710493,0.001103007,0.0001398255,0.00002392199,0.00004076317,0.0001561531,0.0000138783,0.0003020548],"genre_scores_gemma":[0.9975678,0.00012555,0.001948647,0.00001132902,0.00002475609,0.00002567197,0.0002615594,0.0000015453,0.00003303842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004973219,"threshold_uncertainty_score":0.02630121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09828065321670386,"score_gpt":0.385470020832151,"score_spread":0.2871893676154471,"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."}}