{"id":"W4394427921","doi":"10.6084/m9.figshare.21273921","title":"Additional file 8 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; Biology; Genetic correlation; Genetics; Evolutionary biology; Computational biology; Biotechnology; Demography; Psychology; Genetic variation; Mathematics; Gene; Communication; 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":[0.00126782,0.001740646,0.001718068,0.002060055,0.001067856,0.002072681,0.002466178,0.001811041,0.4969637],"category_scores_gemma":[0.01098115,0.0007344287,0.001451767,0.003476025,0.0004102288,0.001036638,0.001355318,0.001386131,0.1106714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000870047,"about_ca_system_score_gemma":0.001688118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01371911,"about_ca_topic_score_gemma":0.02897778,"domain_scores_codex":[0.9992632,0.0001205818,0.00008077475,0.000272543,0.0001320374,0.0001309337],"domain_scores_gemma":[0.99428,0.004127262,0.0003257737,0.0004778865,0.0005349854,0.0002539474],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002721774,0.00007730896,0.006290463,0.002544658,0.0001429451,0.0001029749,0.00007362998,0.0007080484,0.0004077542,0.0006804626,0.9848236,0.003876139],"study_design_scores_gemma":[0.004679757,0.0001705782,0.04725788,0.001544477,0.0004768133,0.0004931468,0.0003093132,0.002034239,0.001380953,0.007847918,0.9336483,0.0001566539],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001256673,0.0000194904,0.00009065751,0.00002805689,0.000006792799,0.00001064736,0.9993407,0.0001594082,0.0002184937],"genre_scores_gemma":[0.002369915,0.00004889541,0.0009750623,0.0001311048,0.0000124425,0.0002762426,0.994468,0.0003051839,0.001413156],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4969637,"threshold_uncertainty_score":0.7175202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159939075063981,"score_gpt":0.2495713078003957,"score_spread":0.2179719170497559,"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."}}