{"id":"W3127811165","doi":"10.1073/pnas.2015772118","title":"Competitive history shapes rapid evolution in a seasonal climate","year":2021,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Competition (biology); Competitor analysis; Ecology; Climate change; Adaptation (eye); Trajectory; Biology; Evolutionary ecology; Evolutionary dynamics; Field (mathematics); Experimental evolution; Evolutionary biology; Population; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002477048,0.0001566029,0.0001592729,0.0002956728,0.0003924686,0.0006760809,0.0001864173,0.0003159669,0.001866869],"category_scores_gemma":[0.000533958,0.000153141,0.0001589672,0.0001699427,0.0002523313,0.0002463146,0.0004346955,0.0003204388,0.0002359816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004755367,"about_ca_system_score_gemma":0.0002948508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002205761,"about_ca_topic_score_gemma":0.007636299,"domain_scores_codex":[0.9998935,0.00001936394,0.000003804972,0.00003556783,0.00001751319,0.00003016019],"domain_scores_gemma":[0.9997957,0.00004154101,0.00004966036,0.00001278877,0.00003178651,0.00006846186],"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":[0.0004693939,0.000161183,0.2045843,0.00006183677,0.0001336928,0.000330595,0.0007105548,0.003465896,0.7572581,0.004251479,0.0008086914,0.02776431],"study_design_scores_gemma":[0.00003349207,0.0003786914,0.9602483,0.00001962718,0.00006042778,0.0008136361,0.0007536376,0.01624644,0.01437815,0.002936668,0.004089215,0.00004166744],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980103,0.00006562923,0.0003768042,0.00005377365,0.00000332835,0.000001568534,0.00003596086,0.00001098842,0.001441751],"genre_scores_gemma":[0.9992931,0.00003181668,0.0001993588,0.00004173423,0.000001895665,0.00000236125,0.00005157791,0.000006364975,0.0003717802],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002205761,"threshold_uncertainty_score":0.006245315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198107692953324,"score_gpt":0.272236157048173,"score_spread":0.2524253877528406,"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."}}