{"id":"W4220935271","doi":"10.1101/2022.03.30.486421","title":"Macroevolutionary diversity of traits and genomes in the model yeast genus <i>Saccharomyces</i>","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Fermentation and Sensory Analysis","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université Laval","funders":"Great Lakes Bioenergy Research Center; National Institutes of Health; National Institute of Food and Agriculture; Division of Graduate Education; Generalitat Valenciana; Universitat de València; University of Wisconsin-Madison; Biological and Environmental Research; National Natural Science Foundation of China; European Commission; Office of Science; Norges Forskningsråd; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Agriculture; National Science Foundation","keywords":"Biology; Evolutionary biology; Phylogenetic tree; Lineage (genetic); Saccharomyces; Genome; Biodiversity; Genus; Phylogenetics; Genetic diversity; Population; Saccharomyces cerevisiae; Genetics; Yeast; Gene; 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":[0.0002640525,0.0002259715,0.000228349,0.001133979,0.0003203307,0.0005044944,0.0002376638,0.0002131699,0.0006371032],"category_scores_gemma":[0.0004541432,0.000124607,0.0003495495,0.001261156,0.000210147,0.0002428973,0.00037274,0.0002748178,0.0002153024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003222964,"about_ca_system_score_gemma":0.0001636938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002482022,"about_ca_topic_score_gemma":0.003131523,"domain_scores_codex":[0.9998618,0.00002591801,0.00001026736,0.00005544842,0.0000282202,0.00001829958],"domain_scores_gemma":[0.9997774,0.0000641189,0.00006113089,0.00004522338,0.00002612234,0.0000260946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001170998,0.0002213616,0.4107725,0.0004349046,0.0004306974,0.0005210197,0.0006850863,0.02592823,0.5152108,0.001863791,0.004161003,0.03859952],"study_design_scores_gemma":[0.0000523466,0.0003331787,0.8622403,0.00007303994,0.0002319175,0.0009658486,0.0009188938,0.04834937,0.06225204,0.002752759,0.02174798,0.00008231507],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993042,0.0002210504,0.001177173,0.00002833428,0.000003405074,0.000003822739,0.005070803,0.00008562727,0.0003678353],"genre_scores_gemma":[0.9629118,0.0003499544,0.006053117,0.00003420797,0.000005851981,0.00001970175,0.0303088,0.00009611638,0.0002205241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002482022,"threshold_uncertainty_score":0.004935086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328913903785685,"score_gpt":0.2016659600462743,"score_spread":0.1783768210084174,"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."}}