{"id":"W6904698194","doi":"10.1371/journal.pone.0212544.g002","title":"Genetic change in hip extended score across 10 generations of selection in Labrador Retrievers.","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Selection (genetic algorithm); Population; Genetic variation; Climate change","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":[0.0006181982,0.0004286056,0.0004304945,0.001118299,0.0005082849,0.0004548309,0.0007869506,0.000865033,0.01616956],"category_scores_gemma":[0.0004723645,0.0002552752,0.0006295866,0.0008169596,0.0002904764,0.0001673871,0.0004708071,0.0008876332,0.004112807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007781431,"about_ca_system_score_gemma":0.0002578038,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02158232,"about_ca_topic_score_gemma":0.04325117,"domain_scores_codex":[0.9995604,0.00006983434,0.00002832787,0.0001513428,0.0001155721,0.00007444468],"domain_scores_gemma":[0.9994354,0.000174769,0.0001068815,0.00006526257,0.00008956197,0.0001281557],"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":[0.003323736,0.001038778,0.03669031,0.0003154684,0.0006829532,0.002225995,0.0006190169,0.001587621,0.8717422,0.001128653,0.0256287,0.05501656],"study_design_scores_gemma":[0.0002211263,0.001368066,0.9173203,0.0001710145,0.0005501286,0.001495264,0.000473259,0.002092399,0.04180401,0.0002699771,0.03409418,0.0001401341],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9184307,0.001148619,0.004344878,0.0004777317,0.0002624882,0.0001782357,0.0420932,0.0009317508,0.03213248],"genre_scores_gemma":[0.8296362,0.0009353232,0.008779567,0.0006349216,0.00004814789,0.0002645699,0.03708056,0.00167145,0.1209492],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02158232,"threshold_uncertainty_score":0.05409253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08681855151402779,"score_gpt":0.3222804551134822,"score_spread":0.2354619035994544,"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."}}