{"id":"W6939729710","doi":"10.6084/m9.figshare.13070932","title":"Additional file 2 of Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle","year":2020,"lang":"en","type":"article","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 Alberta; University of Guelph","funders":"","keywords":"Beef cattle; Pipeline transport; SNP; Pipeline (software)","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":[0.002555645,0.001241765,0.001186836,0.002195505,0.001054105,0.001634466,0.002211627,0.001317229,0.7595006],"category_scores_gemma":[0.01652866,0.0007687741,0.001173752,0.002458106,0.0004201426,0.001312952,0.001097335,0.001147745,0.1663089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008439167,"about_ca_system_score_gemma":0.00147648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005280637,"about_ca_topic_score_gemma":0.01143674,"domain_scores_codex":[0.9989256,0.0001851254,0.0001262654,0.0003383647,0.000289808,0.0001347546],"domain_scores_gemma":[0.9836798,0.01286974,0.0005945005,0.0009596788,0.001514712,0.0003815061],"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":[0.0004980922,0.00008491701,0.002700815,0.002532077,0.00009544872,0.0001219828,0.0001171347,0.001071529,0.001112776,0.0009359375,0.9797249,0.01100438],"study_design_scores_gemma":[0.004318101,0.000370516,0.03659755,0.002077977,0.000358776,0.0007056562,0.0003744141,0.005945815,0.006498023,0.01627188,0.9261636,0.0003176852],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0003045928,0.00002444953,0.001575381,0.00007866377,0.00003562829,0.00006851675,0.9945115,0.002385316,0.001015898],"genre_scores_gemma":[0.0084519,0.00008765521,0.0139779,0.0006683118,0.00009573938,0.001287248,0.9625941,0.005422228,0.007414966],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7595006,"threshold_uncertainty_score":0.3430432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09441448066613078,"score_gpt":0.2937430001017251,"score_spread":0.1993285194355943,"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."}}