{"id":"W1604554928","doi":"10.1111/evo.12739","title":"When maladaptive gene flow does not increase selection","year":2015,"lang":"en","type":"article","venue":"Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene flow; Gasterosteus; Biology; Stickleback; Selection (genetic algorithm); Population; Evolutionary biology; Directional selection; Flow (mathematics); Gene; Ecology; Genetics; Genetic variation; Fishery; Mechanics; Demography; Fish <Actinopterygii>; Computer science","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":[0.001294897,0.0003697888,0.0004846832,0.0003879213,0.0004524131,0.0009860614,0.0005288614,0.00114045,0.00164506],"category_scores_gemma":[0.005088165,0.0002455871,0.0003779793,0.0002896644,0.001109623,0.001205975,0.001391846,0.0005300003,0.0002177023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000533618,"about_ca_system_score_gemma":0.000370433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005675644,"about_ca_topic_score_gemma":0.001328857,"domain_scores_codex":[0.9992489,0.0002773383,0.00004415445,0.0001968731,0.00009007044,0.0001425764],"domain_scores_gemma":[0.998015,0.0007424029,0.0004306253,0.000414336,0.0001289037,0.0002686457],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001146642,0.0005095733,0.4792526,0.0004138077,0.0008678774,0.002629135,0.001094824,0.06382183,0.3549972,0.05404695,0.001567283,0.03965231],"study_design_scores_gemma":[0.0004110218,0.002326819,0.616572,0.00006443089,0.0004945421,0.003405964,0.001596575,0.2403009,0.02298765,0.108091,0.003590311,0.0001589293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993244,0.00009227024,0.00430073,0.0004226918,0.00001757673,0.000006415901,0.00002799959,0.00004503458,0.001843313],"genre_scores_gemma":[0.9990891,0.00003246315,0.0006011367,0.0001136478,0.00001387651,0.000005518048,0.00001858676,0.000005101151,0.0001204908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00164506,"threshold_uncertainty_score":0.006848156,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125026470836425,"score_gpt":0.2159015482121737,"score_spread":0.2033989011285312,"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."}}