{"id":"W2885943266","doi":"10.1093/molbev/msy154","title":"Integrative Population and Physiological Genomics Reveals Mechanisms of Adaptation in Killifish","year":2018,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Natural Sciences and Engineering Research Council of Canada; University of the Western Cape; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; National Science Foundation","keywords":"Biology; Fundulus; Local adaptation; Evolutionary biology; Genome-wide association study; Population; Killifish; Population genomics; Genomics; Genetics; Adaptation (eye); Association mapping; Genome; Genotype; Single-nucleotide polymorphism; 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":[0.0001766431,0.0000787162,0.0001344215,0.00003573335,0.00005498786,0.000001950268,0.00004312973,0.0002037705,0.00004299847],"category_scores_gemma":[0.00005863047,0.00006334039,0.00001610559,0.00007871659,0.0004374359,0.00004274795,0.00006353598,0.00006776538,0.000007034184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006192879,"about_ca_system_score_gemma":0.000003208724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000335615,"about_ca_topic_score_gemma":0.0006269615,"domain_scores_codex":[0.9993103,0.0001478694,0.000155836,0.0002364168,0.00002369993,0.0001258397],"domain_scores_gemma":[0.9998097,0.00001649855,0.00007511495,0.00006472747,0.00001012501,0.00002383929],"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":[0.00003018438,0.00002817931,0.2101296,0.000001637545,0.000002899823,5.571928e-7,0.00008686432,0.00001179805,0.7841349,0.004647653,0.00001916001,0.0009065255],"study_design_scores_gemma":[0.000168736,0.0004482757,0.9106715,0.000004107574,0.000007740473,0.000003958715,0.0001051913,0.0008932535,0.004297291,0.08332192,0.00001039644,0.0000675918],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821736,0.00003890245,0.0173775,0.00008025563,0.00007977778,0.0001394437,0.000005084818,0.000007697868,0.00009774261],"genre_scores_gemma":[0.9967868,0.00002060411,0.003016595,0.0001072414,0.00001180821,0.00001041154,0.00003259137,0.000002751777,0.00001122083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7798377,"threshold_uncertainty_score":0.2582946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01560550485636743,"score_gpt":0.2596082627332839,"score_spread":0.2440027578769164,"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."}}