{"id":"W2009290712","doi":"10.1038/nature13301","title":"Genetics of ecological divergence during speciation","year":2014,"lang":"en","type":"article","venue":"Nature","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":336,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Institute of General Medical Sciences; National Human Genome Research Institute; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Cancer Institute; University of California, Davis","keywords":"Genetic algorithm; Divergence (linguistics); Evolutionary biology; Biology; Ecology; Ecological genetics; Ecological speciation; Genetics; Genetic variation; Gene flow; Gene; Medicine","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":[0.0008335309,0.0002138476,0.0003333709,0.000914605,0.0005916311,0.001042148,0.0004685866,0.0007837086,0.001177475],"category_scores_gemma":[0.001086739,0.0003520754,0.0002548227,0.0006168298,0.001363132,0.001031689,0.0007561352,0.0009945645,0.0001260456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008855568,"about_ca_system_score_gemma":0.0002798844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008843872,"about_ca_topic_score_gemma":0.001644543,"domain_scores_codex":[0.9997097,0.0001010678,0.00001400183,0.00006336077,0.00005698873,0.00005499993],"domain_scores_gemma":[0.999246,0.0003477909,0.0001256723,0.00005683885,0.00007299992,0.0001507014],"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":[0.001226015,0.000244599,0.255501,0.0002304838,0.0004309328,0.001872296,0.003936918,0.01245684,0.6096153,0.06089945,0.0008907099,0.05269545],"study_design_scores_gemma":[0.00008264353,0.000207508,0.9113811,0.00004824969,0.0001165303,0.001795085,0.001617749,0.01071351,0.01904009,0.05098856,0.003927734,0.00008119506],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964737,0.0005296972,0.001373347,0.0002461765,0.0000101716,0.000002723832,0.00002769055,0.0000150786,0.001321369],"genre_scores_gemma":[0.9991036,0.0001455129,0.0003999773,0.00005092901,0.00001042462,0.000002268089,0.00002663507,0.000007840029,0.0002527063],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001177475,"threshold_uncertainty_score":0.006425202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005394584752000085,"score_gpt":0.2226573180859346,"score_spread":0.2172627333339345,"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."}}