{"id":"W2561154863","doi":"10.14348/molcells.2016.0219","title":"Detecting Positive Selection of Korean Native Goat Populations Using Next-Generation Sequencing","year":2016,"lang":"en","type":"article","venue":"Molecules and Cells","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Biotechnology Research Institute","funders":"Rural Development Administration","keywords":"Biology; Crossbreed; Capra hircus; Korean Native; Genome; Domestication; Population; Genetic diversity; Genetics; Haplotype; Evolutionary biology; Gene; Zoology; Genotype; Food 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007249394,0.000220198,0.0002471252,0.0005273768,0.0002399743,0.0004784443,0.0002339379,0.0002684662,0.0004632147],"category_scores_gemma":[0.000738795,0.0001316691,0.0003019284,0.0003748508,0.0002200425,0.0002112427,0.0002704188,0.0002085327,0.0001149055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001939056,"about_ca_system_score_gemma":0.0002169199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002332513,"about_ca_topic_score_gemma":0.004790605,"domain_scores_codex":[0.9997368,0.00006179332,0.00001587383,0.0000944256,0.00005486601,0.00003630577],"domain_scores_gemma":[0.9996836,0.0001065765,0.00008030368,0.00002657156,0.00007215999,0.00003073571],"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":[0.0003369465,0.0001057287,0.331764,0.0003908805,0.0004652425,0.000903003,0.001381071,0.001121255,0.625654,0.0007614098,0.0009879321,0.03612846],"study_design_scores_gemma":[0.00006871005,0.0003166097,0.922599,0.00008090496,0.0005520604,0.001355691,0.001245604,0.01002509,0.04990208,0.0007496899,0.01304208,0.00006262269],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908031,0.001167538,0.006104105,0.00009567385,0.00002263384,0.00003473385,0.0008568108,0.00004343467,0.0008719095],"genre_scores_gemma":[0.9818192,0.000647611,0.01410565,0.0003022272,0.00001863278,0.00007876868,0.002323704,0.00003058112,0.0006736476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002332513,"threshold_uncertainty_score":0.004637837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04268317183177832,"score_gpt":0.2539333489917702,"score_spread":0.2112501771599918,"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."}}