{"id":"W1939134820","doi":"10.1111/evo.12237","title":"INTEGRATING LANDSCAPE GENOMICS AND SPATIALLY EXPLICIT APPROACHES TO DETECT LOCI UNDER SELECTION IN CLINAL POPULATIONS","year":2013,"lang":"en","type":"article","venue":"Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Lethbridge","funders":"","keywords":"Cline (biology); Biology; Population genomics; Genomics; Selection (genetic algorithm); Population; Local adaptation; Evolutionary biology; Locus (genetics); Directional selection; Genome; Genetics; Genetic variation; Artificial intelligence; Computer science; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001733783,0.0003866721,0.0003898578,0.001763396,0.0003166464,0.000844562,0.0005585095,0.0004316957,0.0005031576],"category_scores_gemma":[0.003216391,0.0002596876,0.0003134553,0.0009686776,0.0004825396,0.0007559501,0.0009256035,0.0005539876,0.00007229846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000417753,"about_ca_system_score_gemma":0.0002747822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001919299,"about_ca_topic_score_gemma":0.005988678,"domain_scores_codex":[0.9991575,0.0004574827,0.00003240443,0.0002056753,0.0001026811,0.00004423348],"domain_scores_gemma":[0.9979668,0.001248699,0.0003409844,0.0001881003,0.0001793466,0.00007606631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004712936,0.0004674529,0.4215536,0.0003929871,0.001386203,0.0004109284,0.001332982,0.08153177,0.2331815,0.009224758,0.0003127082,0.2497339],"study_design_scores_gemma":[0.0001111318,0.0003933857,0.6143925,0.00005508192,0.0003064033,0.0005379745,0.0008635388,0.3410397,0.02088266,0.01969343,0.001570704,0.0001534968],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8759722,0.0002474468,0.1220809,0.0001135893,0.000009108541,0.00004228054,0.0001670589,0.0001698412,0.001197631],"genre_scores_gemma":[0.9539043,0.00007744587,0.0456724,0.00005106724,0.000006264061,0.00003618899,0.00009475229,0.00001942496,0.0001381351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001919299,"threshold_uncertainty_score":0.009169221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04389208798849478,"score_gpt":0.2333120453826616,"score_spread":0.1894199573941668,"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."}}