{"id":"W2884047901","doi":"10.1111/mec.14808","title":"On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system","year":2018,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Australian Research Council; Flinders University","keywords":"Biology; Biological dispersal; Local adaptation; Ecology; Population genomics; Gene flow; Population; Genetic variation; Adaptation (eye); Evolutionary biology; Genomics; Gene; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00008423802,0.00007787858,0.00009927418,0.00006184953,0.00003698483,0.000005997306,0.00007347138,0.0001355878,0.00001402643],"category_scores_gemma":[0.00002153074,0.00006982529,0.00002029089,0.00003881217,0.00004488192,0.000002016515,0.00006000196,0.00005089087,0.000001031128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002058054,"about_ca_system_score_gemma":0.000009307548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001742105,"about_ca_topic_score_gemma":0.001398147,"domain_scores_codex":[0.9993861,0.0001266852,0.0001434501,0.0001847946,0.00005237103,0.0001065636],"domain_scores_gemma":[0.999763,0.00001272889,0.0000664021,0.0001338776,0.000007070771,0.00001699579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004676723,0.00001176016,0.5941389,0.00001081487,0.00001291658,0.000004818855,0.000176717,0.001069124,0.4039122,0.0003912671,0.000002704162,0.0002221199],"study_design_scores_gemma":[0.0003926978,0.000156113,0.9776448,0.000007399617,0.000008659354,0.00001794413,0.0001361345,0.001159157,0.02020401,0.0001915343,0.00001391748,0.00006763409],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995368,0.0000697714,0.0001170433,0.00002406312,0.00006263615,0.0001361951,0.00002026934,0.00000186658,0.00003142976],"genre_scores_gemma":[0.9996658,0.000004233378,0.0001262752,0.0001091936,0.0000213659,0.000003402402,0.00006168614,0.00000586171,0.000002177499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3837081,"threshold_uncertainty_score":0.2847393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004160743051526456,"score_gpt":0.1944408837025917,"score_spread":0.1902801406510652,"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."}}