{"id":"W2138655328","doi":"10.1038/ncomms2814","title":"The genomics of selection in dogs and the parallel evolution between dogs and humans","year":2013,"lang":"en","type":"article","venue":"Nature Communications","topic":"Human-Animal Interaction Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":328,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"National Key Research and Development Program of China; Knut och Alice Wallenbergs Stiftelse; National Natural Science Foundation of China; Chinese Academy of Sciences; Royal Swedish Academy of Sciences","keywords":"Domestication; Biology; Selection (genetic algorithm); Genomics; Genome; Evolutionary biology; Population; Gene; Molecular evolution; Genetics; Medicine; Computer science","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":[0.0002160936,0.00005975203,0.00007975632,0.000022607,0.0003271944,0.00002650535,0.0002368408,0.0001116046,0.000001894283],"category_scores_gemma":[0.0001193339,0.0000382784,0.00002388254,0.00006071798,0.0003503304,0.000006529465,0.0002550243,0.000297358,0.000001599067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001772187,"about_ca_system_score_gemma":0.00001431641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003125623,"about_ca_topic_score_gemma":0.004709662,"domain_scores_codex":[0.9995061,0.0001347443,0.0001529701,0.00009214314,0.00004145586,0.00007263826],"domain_scores_gemma":[0.9992813,0.0001617252,0.00008266312,0.000346134,0.0001151876,0.00001293801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002649904,0.0001855583,0.5507741,0.00003604626,0.0006781219,7.246731e-8,0.003802524,0.00004937961,0.2964178,0.1211554,0.01963907,0.00699694],"study_design_scores_gemma":[0.0007289913,0.00006302925,0.9289868,0.00001005245,0.00003792251,0.000003889841,0.0006940558,0.0003070968,0.0009546553,0.002553507,0.06555337,0.0001066069],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769546,0.0164495,0.0001168911,0.004767724,0.00002589596,0.0003167826,0.000005615892,0.00000552844,0.001357435],"genre_scores_gemma":[0.9953339,0.003870353,0.0004551428,0.00007905799,0.00003464882,0.00006295933,0.00001467387,0.000005233628,0.0001440417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3782127,"threshold_uncertainty_score":0.2628102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01700905898093995,"score_gpt":0.3318631283762504,"score_spread":0.3148540693953104,"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."}}