{"id":"W4253395857","doi":"10.1016/s0378-1097(01)00362-7","title":"Predicting the emergence of resistance to antifungal drugs","year":2001,"lang":"en","type":"article","venue":"FEMS Microbiology Letters","topic":"Antifungal resistance and susceptibility","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biology; Fitness landscape; Context (archaeology); Genetics; Genome; Gene; Human evolutionary genetics; Resistance (ecology); Antifungal; Adaptation (eye); Antifungal drug; Genetic Fitness; Allele; Drug resistance; Adaptive evolution; Evolutionary biology; Ecology; Population; Microbiology","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":[0.000961027,0.0003037274,0.000341144,0.0008674887,0.0002317856,0.0007975047,0.000381217,0.0009110928,0.001202915],"category_scores_gemma":[0.007439706,0.0002093303,0.0002499398,0.0003187985,0.0003750453,0.0006534811,0.0002902524,0.0009800601,0.0002803483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00038836,"about_ca_system_score_gemma":0.0002791172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006874583,"about_ca_topic_score_gemma":0.0009911999,"domain_scores_codex":[0.9995809,0.000211816,0.00003562959,0.00008605648,0.00005286282,0.00003270294],"domain_scores_gemma":[0.9953346,0.003684231,0.0004006128,0.0001770707,0.0002811913,0.0001223264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009926192,0.0004196393,0.5383605,0.000245408,0.0001516019,0.0006851408,0.0001141564,0.2165723,0.04281129,0.006228021,0.001964728,0.1914546],"study_design_scores_gemma":[0.00007176898,0.000641835,0.08710007,0.00004244498,0.00009310512,0.001063272,0.0002434517,0.8596984,0.03171337,0.01622573,0.003054717,0.00005195714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9416215,0.0009779345,0.05221682,0.001189988,0.00006140737,0.00004059165,0.0004693111,0.0002993565,0.003123148],"genre_scores_gemma":[0.9741213,0.0004812985,0.02435913,0.0001544633,0.00004898371,0.00002161845,0.0004752004,0.00001392633,0.000324033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001202915,"threshold_uncertainty_score":0.005082428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01183230872327235,"score_gpt":0.2580882416127926,"score_spread":0.2462559328895202,"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."}}