{"id":"W3016019886","doi":"10.1007/s10142-020-00738-9","title":"Use of gene expression profile to identify potentially relevant transcripts to myofibrillar fragmentation index trait","year":2020,"lang":"en","type":"article","venue":"Functional & Integrative Genomics","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Biology; Transcriptome; Gene; Myosin; Myofibril; Gene expression; Tenderness; Gene expression profiling; RNA-Seq; Genetics; Candidate gene; Cell biology; Biochemistry; Food science","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":[],"consensus_categories":[],"category_scores_codex":[0.0001573704,0.0003035436,0.0002852069,0.0005936974,0.0002343674,0.0003237428,0.0001349741,0.0002347519,0.001037386],"category_scores_gemma":[0.0002255862,0.000133728,0.0003641986,0.0006296592,0.0001357808,0.0001487382,0.0001935537,0.0004277201,0.0003177747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001827435,"about_ca_system_score_gemma":0.0002326888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001081186,"about_ca_topic_score_gemma":0.002041978,"domain_scores_codex":[0.9998916,0.00000864159,0.000004948715,0.00005381493,0.00002084687,0.00002006331],"domain_scores_gemma":[0.9998535,0.0000550617,0.00003260553,0.000008918642,0.00002676858,0.00002303225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008248151,0.00001983839,0.003980877,0.00002598254,0.000009871138,0.00003632346,0.00002549788,0.00007244342,0.9928433,0.00004194663,0.00002392567,0.002837498],"study_design_scores_gemma":[0.00004036042,0.0006341328,0.3923561,0.00001952227,0.0002270992,0.0008081681,0.0002870221,0.0101195,0.5916061,0.0004068838,0.003457607,0.00003750098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9692221,0.0007419212,0.0243234,0.0001000488,0.00002828489,0.00008950973,0.00320858,0.0001670443,0.002119009],"genre_scores_gemma":[0.9553802,0.0005698443,0.0330531,0.0002444297,0.00002472601,0.0002228994,0.00610093,0.00005537088,0.004348484],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001081186,"threshold_uncertainty_score":0.003470421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08766335635264348,"score_gpt":0.2768514412925743,"score_spread":0.1891880849399308,"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."}}