{"id":"W2332171014","doi":"","title":"quantitative traits Data from selective harvests underestimate temporal trends in","year":2012,"lang":"en","type":"article","venue":"","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Trophy; Selection (genetic algorithm); Population; Geography; Biology; Demography; Computer science; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006728513,0.0005373258,0.0003865785,0.001287171,0.0004163073,0.001004221,0.000590119,0.0005155936,0.003117848],"category_scores_gemma":[0.01211399,0.0002680639,0.0003544805,0.002349592,0.0005592606,0.001070274,0.0006565489,0.0005784701,0.001303147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003102639,"about_ca_system_score_gemma":0.0001746955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00225685,"about_ca_topic_score_gemma":0.005144568,"domain_scores_codex":[0.9969825,0.0006539296,0.0003441943,0.0007009906,0.001175291,0.0001430692],"domain_scores_gemma":[0.9796653,0.005291867,0.009686443,0.002491503,0.0025545,0.0003104241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009977986,0.00007004787,0.9597741,0.0001157177,0.0003087678,0.00003697401,0.0003655583,0.0005824202,0.004526566,0.0002595332,0.001394909,0.03246558],"study_design_scores_gemma":[0.000002218041,0.00006702452,0.9959329,0.0000217875,0.00002810577,0.000125049,0.000141896,0.0009028312,0.0005275055,0.0003037176,0.001939759,0.000007199583],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9365042,0.003170381,0.04028259,0.0006010936,0.0002086159,0.0001308327,0.008675056,0.0002667241,0.01016042],"genre_scores_gemma":[0.9813156,0.0006689491,0.007943066,0.0004875321,0.0001717368,0.0001351805,0.006703532,0.00005353234,0.002521016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006728513,"threshold_uncertainty_score":0.03558421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07270035767566486,"score_gpt":0.337161930638981,"score_spread":0.2644615729633162,"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."}}