{"id":"W3024098066","doi":"10.1101/2020.05.13.091124","title":"The Evolution and Fate of Diversity Under Hard and Soft Selection","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selection (genetic algorithm); Evolutionary biology; Natural selection; Population; Diversification (marketing strategy); Niche; Biology; Frequency-dependent selection; Genetic diversity; Ecology; Computer science; Artificial intelligence; Demography","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":[0.0005158945,0.0001378167,0.0002697228,0.0003407055,0.0002335568,0.0009873243,0.0002985072,0.0003589566,0.001349598],"category_scores_gemma":[0.001150372,0.0001290318,0.0001936026,0.0001724689,0.000845328,0.0004595577,0.0008303227,0.00061131,0.0001975364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003220669,"about_ca_system_score_gemma":0.0001331054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003276212,"about_ca_topic_score_gemma":0.0004712173,"domain_scores_codex":[0.9997676,0.00004981279,0.00001487649,0.00005865503,0.00006957305,0.00003944009],"domain_scores_gemma":[0.999051,0.0002827046,0.0002839197,0.0001156764,0.00009053845,0.0001761294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002960769,0.00006034593,0.07489948,0.00005237942,0.00008326412,0.0002169895,0.000198022,0.002655724,0.9078865,0.002652098,0.0001304802,0.01086865],"study_design_scores_gemma":[0.00004473126,0.0008044888,0.7900867,0.00002941344,0.0001035864,0.0009955744,0.0009989935,0.04467932,0.1500073,0.01044555,0.001707011,0.00009718157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984667,0.00004935773,0.0007479531,0.00004050511,0.000002326143,0.000001498143,0.00001860684,0.000008627384,0.000664382],"genre_scores_gemma":[0.9995114,0.00001780939,0.0002237954,0.00002515647,0.000002639486,0.000002105512,0.00001783364,0.000004559209,0.000194733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001349598,"threshold_uncertainty_score":0.004514873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01165298852547507,"score_gpt":0.208774246535495,"score_spread":0.19712125801002,"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."}}