{"id":"W4394378424","doi":"10.6084/m9.figshare.21273906","title":"Additional file 3 of Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Affect (linguistics); Correlation; Fertility; Evolutionary biology; Biology; Genetic correlation; Genetics; Computational biology; Psychology; Mathematics; Genetic variation; Demography; Communication; Gene; Sociology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001232117,0.001523944,0.00147756,0.001746122,0.0009363818,0.00181104,0.002297007,0.001451955,0.5347662],"category_scores_gemma":[0.009892654,0.0006514324,0.00117331,0.00316207,0.0003997617,0.001013273,0.001323811,0.001231286,0.1250503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007450507,"about_ca_system_score_gemma":0.001441915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01121843,"about_ca_topic_score_gemma":0.02507157,"domain_scores_codex":[0.9993537,0.0001098475,0.00007299952,0.0002428275,0.0001081754,0.0001124626],"domain_scores_gemma":[0.9954035,0.003200049,0.0003013375,0.0004250593,0.0004533101,0.0002167883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001940782,0.00006040509,0.005904719,0.001531429,0.00008816038,0.00007578317,0.00006002162,0.0005991416,0.000244793,0.0006227488,0.9872131,0.003405748],"study_design_scores_gemma":[0.003008393,0.0001354945,0.04275909,0.001135104,0.0003108157,0.0004637305,0.0002764752,0.001905945,0.001141207,0.007327546,0.9414101,0.0001260952],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001239106,0.00001205371,0.000096112,0.00002252224,0.000005748145,0.000009981041,0.9993869,0.0001370741,0.0002055944],"genre_scores_gemma":[0.002089842,0.00003164955,0.0009552023,0.0001068984,0.00001136309,0.000244359,0.9948745,0.0002979261,0.00138817],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5347662,"threshold_uncertainty_score":0.6635996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03158354915547038,"score_gpt":0.2494318834461869,"score_spread":0.2178483342907165,"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."}}