{"id":"W4282980347","doi":"10.1016/j.livsci.2022.104995","title":"Transcriptome profile in the skeletal muscle of cattle progeny as a function of maternal protein supplementation during mid-gestation","year":2022,"lang":"en","type":"article","venue":"Livestock Science","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Instituto Nacional de Ciência e Tecnologia de Ciência Animal; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Biology; Skeletal muscle; Offspring; Transcriptome; Gene; Gestation; Internal medicine; Endocrinology; Andrology; Cell biology; Genetics; Gene expression; Medicine; Pregnancy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002416575,0.00004782662,0.00004831972,0.00005552647,0.0001270776,0.000004600567,0.0001932674,0.00001538961,0.00006377516],"category_scores_gemma":[0.00001765734,0.0000414918,0.00002481794,0.0002259207,0.0001691336,0.00001295825,0.00004370014,0.00004812992,8.172514e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009693702,"about_ca_system_score_gemma":0.00009474975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009505105,"about_ca_topic_score_gemma":0.00001987057,"domain_scores_codex":[0.9993231,0.00007159893,0.0001332972,0.0001692996,0.000187215,0.0001155472],"domain_scores_gemma":[0.9997469,0.000003467069,0.00008550664,0.0001206324,0.00003033543,0.00001322113],"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":[0.00009650987,0.0000812118,0.001755449,0.00002548404,0.000002311928,1.816353e-7,0.0006697441,0.000405712,0.9962231,0.0003148787,0.000005577553,0.0004198634],"study_design_scores_gemma":[0.0003431017,0.0007070213,0.4840262,0.000004312254,0.000003381951,0.00000258838,0.00116163,0.00002159419,0.5133918,0.0002278017,0.00006546749,0.00004508039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999115,0.00003661303,0.00009681415,0.00004935843,0.00004247265,0.0004364922,0.0000178604,0.000002227775,0.0002030909],"genre_scores_gemma":[0.9995324,0.000001874675,0.000130144,0.0000226316,0.000009216467,0.0002073119,0.00003775121,0.000003006904,0.00005565767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4828313,"threshold_uncertainty_score":0.1691986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007481301769969767,"score_gpt":0.247161133045071,"score_spread":0.2396798312751012,"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."}}