{"id":"W4390120279","doi":"10.1093/mmy/myad134","title":"Machine learning to identify clinically relevant <i>Candida</i> yeast species","year":2023,"lang":"en","type":"article","venue":"Medical Mycology","topic":"Antifungal resistance and susceptibility","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canada Foundation for Innovation; Government of Alberta","keywords":"Candida albicans; Budding yeast; Candida glabrata; Yeast; Biology; Corpus albicans; Candida auris; Convolutional neural network; Artificial intelligence; Microbiology; Candida infections; Antifungal; Saccharomyces cerevisiae; Computer science; Biochemistry","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":[0.0007383325,0.0009270024,0.0003890256,0.0008588957,0.0001836257,0.0007031635,0.0004802569,0.0006241071,0.0008055822],"category_scores_gemma":[0.001620709,0.0002044919,0.0004962497,0.0004056476,0.0001931259,0.0005216813,0.0003598468,0.0005089115,0.0004112629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006131139,"about_ca_system_score_gemma":0.0005741527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006546807,"about_ca_topic_score_gemma":0.008003195,"domain_scores_codex":[0.9997428,0.00004670326,0.00001963476,0.00006370321,0.00006541464,0.00006164137],"domain_scores_gemma":[0.9995404,0.0001545084,0.00008304755,0.00003793772,0.000152691,0.00003141557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001143132,0.0006096652,0.1267062,0.0005300062,0.0003794159,0.0005983876,0.0001021792,0.1984413,0.0950172,0.001131461,0.007542145,0.5677988],"study_design_scores_gemma":[0.00001838551,0.0002385829,0.01921083,0.00005940463,0.0001061501,0.0003785359,0.00005296816,0.9457386,0.03145437,0.0007587784,0.001960522,0.00002292637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8967904,0.005867311,0.08733056,0.0007298891,0.0001911352,0.0001088082,0.001075716,0.0016508,0.006255386],"genre_scores_gemma":[0.9620077,0.001065549,0.03359694,0.0002461488,0.00003388132,0.00002939844,0.001312532,0.00003373848,0.001674216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006546807,"threshold_uncertainty_score":0.01301736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03059813290932772,"score_gpt":0.3647091864544804,"score_spread":0.3341110535451527,"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."}}