{"id":"W2141376729","doi":"10.1111/mec.12720","title":"The genomic signature of parallel adaptation from shared genetic variation","year":2014,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Freiwillige Akademische Gesellschaft; Universität Basel; European Research Council; National Institutes of Health; National Science Foundation","keywords":"Biology; Locus (genetics); Evolutionary biology; Local adaptation; Haplotype; Divergence (linguistics); Gene flow; Introgression; Genetics; Genetic divergence; Adaptation (eye); Population genomics; Population; Genetic variation; Genome; Genomics; Genetic diversity; Allele; Gene","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":[0.00009690742,0.00009922901,0.0001067172,0.0000228827,0.0001022123,0.00001524396,0.0002143259,0.000219338,0.00004951275],"category_scores_gemma":[0.00008884279,0.00008746191,0.00006866174,0.00004724202,0.00005637962,0.000001778149,0.00007801138,0.00006732187,0.00001289802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008023806,"about_ca_system_score_gemma":0.00003643511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004398362,"about_ca_topic_score_gemma":0.0001285081,"domain_scores_codex":[0.9991944,0.0001656594,0.0001789602,0.0002265111,0.00009088558,0.0001435714],"domain_scores_gemma":[0.9994168,0.00003020566,0.0001403913,0.0002918259,0.00008439392,0.00003641714],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001420558,0.0000272135,0.01002907,0.000007513444,0.0001559494,0.000002231084,0.0003125485,0.04511755,0.9358069,0.002160661,0.0008787611,0.005359554],"study_design_scores_gemma":[0.0009405196,0.0002809121,0.9479623,0.000002746369,0.00007255006,0.0000044811,0.00007303285,0.005901403,0.01643122,0.005310903,0.02281651,0.0002034083],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228514,0.0003899822,0.0758573,0.0002294434,0.000239721,0.0001472091,0.00002348205,0.000006039531,0.0002554407],"genre_scores_gemma":[0.9916751,0.00003716355,0.007419374,0.0003578417,0.00008501535,0.000008028726,0.000266197,0.00001061703,0.0001406526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9379333,"threshold_uncertainty_score":0.3566593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005789894315346506,"score_gpt":0.1932782186660082,"score_spread":0.1874883243506617,"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."}}