{"id":"W4383875446","doi":"10.1016/j.tpb.2023.07.002","title":"Evolutionary dynamics of dispersal and local adaptation in multi-resource landscapes","year":2023,"lang":"en","type":"article","venue":"Theoretical Population Biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; Compute Canada","keywords":"Biological dispersal; Adaptation (eye); Local adaptation; Ecology; Resource (disambiguation); Dynamics (music); Evolutionary dynamics; Biology; Evolutionary biology; Geography; Computer science; Population; Demography; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001783822,0.00008504079,0.0001182166,0.00009048376,0.00002846646,0.000002418527,0.00006290634,0.0001773254,0.0000185413],"category_scores_gemma":[0.0001139087,0.00007960705,0.00003109747,0.0001396174,0.0003280656,0.000002062976,0.00007348425,0.00005789517,0.000005014846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001599304,"about_ca_system_score_gemma":0.0000131901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005021698,"about_ca_topic_score_gemma":0.0003845948,"domain_scores_codex":[0.9992525,0.0001187529,0.0002158149,0.0002064505,0.00005090228,0.0001556054],"domain_scores_gemma":[0.9997345,0.00003371322,0.00004630466,0.0001147069,0.00002802194,0.00004282075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000228653,0.00007848551,0.1915444,0.0000230269,0.00002007629,0.000001076359,0.0001146342,0.02622157,0.005840554,0.7678559,0.00007455036,0.007997071],"study_design_scores_gemma":[0.0004722431,0.0001231082,0.1836628,0.000005803095,0.000005546661,0.000004270198,0.0002441541,0.8014126,0.0000508173,0.01382541,0.00009954325,0.00009374812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8746639,0.0001390713,0.124385,0.0003539431,0.00004882648,0.0001063607,0.00004402488,0.00002011132,0.0002387801],"genre_scores_gemma":[0.9971138,0.00006599347,0.0008834018,0.00004367634,0.00002543641,0.000005933987,0.001804239,0.000009579842,0.00004789889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.775191,"threshold_uncertainty_score":0.3246281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009110359931523742,"score_gpt":0.266601700626335,"score_spread":0.2574913406948112,"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."}}