{"id":"W3215156790","doi":"10.1101/2021.11.29.469899","title":"Asymmetrical dose-responses shape the evolutionary trade-off between antifungal resistance and nutrient use","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Fungal and yeast genetics research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; PROTEO","funders":"National Institute of Allergy and Infectious Diseases; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; University of California, San Francisco; National Institutes of Health","keywords":"Cytosine deaminase; Biology; Trade-off; Deamination; Gene; Genetics; Missense mutation; Drug resistance; Function (biology); Mutation; Enzyme; Biochemistry; Ecology","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":[0.0005899438,0.0002662242,0.0003978276,0.000483245,0.0001643231,0.0007659594,0.0003716056,0.0008481689,0.002020029],"category_scores_gemma":[0.001738236,0.0002010162,0.0002573343,0.0003878473,0.0005065526,0.0003835034,0.0004386073,0.00083207,0.0004325335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000502051,"about_ca_system_score_gemma":0.0001555498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006031647,"about_ca_topic_score_gemma":0.0005533709,"domain_scores_codex":[0.9995133,0.0001195168,0.00002408365,0.0001371391,0.0001511366,0.00005489069],"domain_scores_gemma":[0.9991027,0.0004435785,0.000192322,0.0001139004,0.00008749268,0.0000599268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004280891,0.00008165884,0.02114464,0.00009037251,0.00006551568,0.0001273012,0.00005971406,0.006798748,0.9562817,0.001401827,0.0004264328,0.01309402],"study_design_scores_gemma":[0.00006508579,0.0007706626,0.2170732,0.00003411349,0.0001179898,0.001265189,0.0003287271,0.07126367,0.6970299,0.006323998,0.005636602,0.00009091277],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9896724,0.0006340448,0.006842888,0.000181162,0.00001853351,0.000009334668,0.0004542587,0.0001448373,0.002042381],"genre_scores_gemma":[0.9968272,0.0001750123,0.002135066,0.0001096411,0.000005381939,0.00001123759,0.0001720288,0.00004182452,0.0005226557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002020029,"threshold_uncertainty_score":0.006757677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02308998333748614,"score_gpt":0.2516105016530524,"score_spread":0.2285205183155663,"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."}}