{"id":"W3187063758","doi":"10.2196/24651","title":"Candidemia Risk Prediction (CanDETEC) Model for Patients With Malignancy: Model Development and Validation in a Single-Center Retrospective Study","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Pharmacovigilance and Adverse Drug Reactions","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Korea Health Industry Development Institute","keywords":"Medicine; Random forest; Retrospective cohort study; Receiver operating characteristic; Logistic regression; Machine learning; Artificial intelligence; Cancer; Internal medicine; Algorithm; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01737578,0.001206198,0.00166878,0.001823817,0.0004501469,0.001408253,0.001413217,0.0008797835,0.001019159],"category_scores_gemma":[0.01950734,0.0005437741,0.002428354,0.0008526763,0.0003732531,0.0006026258,0.0008816044,0.001490763,0.0002302401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001492,"about_ca_system_score_gemma":0.001667746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017555,"about_ca_topic_score_gemma":0.004536805,"domain_scores_codex":[0.9974504,0.001483398,0.0001982566,0.0005108029,0.0002144941,0.0001426387],"domain_scores_gemma":[0.9824551,0.01332963,0.001121731,0.0010242,0.001706919,0.0003624733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003903206,0.0009750294,0.7012886,0.0002200143,0.002228517,0.0004370766,0.0002025477,0.2536472,0.0007301094,0.0006249073,0.00150629,0.03423651],"study_design_scores_gemma":[0.0001194251,0.0006518177,0.03038278,0.00003951719,0.0004028248,0.0001946479,0.00007073177,0.967178,0.0003932411,0.0003080287,0.0002350651,0.00002385787],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737927,0.0007227801,0.02344394,0.0002435706,0.00003747891,0.0002589465,0.001026404,0.0001661798,0.0003078728],"genre_scores_gemma":[0.9843918,0.0002032235,0.01366937,0.00004669089,0.00001665603,0.0001813745,0.001355847,0.00001285611,0.0001221892],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01737578,"threshold_uncertainty_score":0.09189302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0641049387357311,"score_gpt":0.380426749508448,"score_spread":0.3163218107727169,"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."}}