{"id":"W6960881728","doi":"10.1371/journal.pone.0238921.t003","title":"Effect of birth order on the milk composition of purebred Quarter Horse mares (means ± standard deviation).","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Purebred; Quarter (Canadian coin); Horse; Composition (language); Birth order","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":[0.001194182,0.001268845,0.001707875,0.0014695,0.0005487543,0.001309778,0.001956206,0.001451034,0.06967171],"category_scores_gemma":[0.007013167,0.0004715034,0.001425179,0.002663214,0.0002687118,0.000747173,0.001350738,0.001374397,0.02931914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007062901,"about_ca_system_score_gemma":0.0009965184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03236854,"about_ca_topic_score_gemma":0.06320617,"domain_scores_codex":[0.9993861,0.0001272724,0.00005983927,0.0002519736,0.00008580626,0.00008906754],"domain_scores_gemma":[0.9972032,0.001426724,0.0004383778,0.0003417822,0.0003826445,0.0002072216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004011983,0.00004313207,0.01913141,0.002477418,0.0005808448,0.00005061367,0.00005887953,0.0006197684,0.0003242586,0.0005839872,0.9707105,0.005017972],"study_design_scores_gemma":[0.001973758,0.0001224001,0.1801264,0.002106598,0.001213511,0.0003302402,0.0003141659,0.001420306,0.0006711992,0.002419394,0.8091821,0.0001199355],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006066556,0.0001535617,0.00004948378,0.00006596834,0.00001674359,0.000003345694,0.9987491,0.00008942845,0.0002656345],"genre_scores_gemma":[0.00561862,0.0001616024,0.0004335951,0.0001569906,0.00001376781,0.00008631254,0.9920502,0.0001219772,0.001357029],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06967171,"threshold_uncertainty_score":0.2330751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194928060013994,"score_gpt":0.2329809907231156,"score_spread":0.2210317101229757,"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."}}