{"id":"W2102333201","doi":"10.1111/j.1558-5646.2009.00665.x","title":"VARIABLE PROGRESS TOWARD ECOLOGICAL SPECIATION IN PARAPATRY: STICKLEBACK ACROSS EIGHT LAKE-STREAM TRANSITIONS","year":2009,"lang":"en","type":"article","venue":"Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":202,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Génome Québec; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Parapatric speciation; Biology; Allopatric speciation; Ecological speciation; Stickleback; Ecology; Genetic algorithm; Sympatric speciation; Ecotone; Incipient speciation; Reproductive isolation; Biological dispersal; Evolutionary biology; Character displacement; Gene flow; Sympatry; Habitat; Genetic variation; Population","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":[0.0003459929,0.0001014092,0.0001967285,0.0007016992,0.0003895354,0.0004367516,0.0001544039,0.0002216954,0.0006087715],"category_scores_gemma":[0.0006886454,0.00008123957,0.0001255991,0.0003301065,0.0004315332,0.0002571243,0.0004627429,0.0001757427,0.00006037441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002987336,"about_ca_system_score_gemma":0.0001262583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00150477,"about_ca_topic_score_gemma":0.004339041,"domain_scores_codex":[0.9999169,0.0000187836,0.000008337062,0.00002562499,0.00001381529,0.0000164814],"domain_scores_gemma":[0.9996346,0.00009441261,0.000126329,0.00003062625,0.00004085893,0.00007311557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007159343,0.00008213132,0.8782982,0.00005526028,0.0002079515,0.0003224855,0.001956229,0.001809384,0.1019934,0.0005482007,0.000101534,0.01390931],"study_design_scores_gemma":[0.000008806129,0.00008547871,0.996869,0.000004486374,0.00002606414,0.0001178297,0.0002775682,0.00108105,0.001197245,0.000216506,0.0001069219,0.000008970073],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998988,0.0000133249,0.00003295128,0.000002520495,1.585466e-7,4.544731e-7,0.00000720113,0.000001426978,0.00004317593],"genre_scores_gemma":[0.9998665,0.000008976289,0.00005777804,0.000003517975,4.782323e-7,0.000001020469,0.00003237132,7.423668e-7,0.0000286301],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00150477,"threshold_uncertainty_score":0.002992034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01045605485042517,"score_gpt":0.2502088020406447,"score_spread":0.2397527471902196,"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."}}