{"id":"W4413021998","doi":"10.1002/mrd.70045","title":"microRNAs for qPCR Normalization Under Morphofunctional Conditions in Bovine Sperm (<i>Bos taurus</i>)","year":2025,"lang":"en","type":"article","venue":"Molecular Reproduction and Development","topic":"MicroRNA in disease regulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Insemination Center of Quebec","funders":"Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Centers for Disease Control and Prevention; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Biology; microRNA; Normalization (sociology); Centralizer and normalizer; Semen; Sperm; Computational biology; Real-time polymerase chain reaction; Small RNA; Sperm motility; Semen quality; Genetics; Gene","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":[0.003320093,0.001327525,0.001363962,0.001519543,0.001405696,0.001442071,0.0008092687,0.001033714,0.003993998],"category_scores_gemma":[0.003593362,0.001094808,0.001179403,0.001862582,0.001222752,0.0007907999,0.0006933722,0.00180508,0.002307443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008414095,"about_ca_system_score_gemma":0.001295544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001500421,"about_ca_topic_score_gemma":0.003877728,"domain_scores_codex":[0.9946486,0.0008732667,0.0006057441,0.002205366,0.001393047,0.0002738605],"domain_scores_gemma":[0.9986671,0.000376408,0.0002964851,0.0001552623,0.0004679674,0.0000368102],"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":[0.0001700295,0.00007334074,0.001139073,0.0004903137,0.00003387884,0.00006371687,0.000387466,0.0004074595,0.9870952,0.0006656239,0.000370328,0.009103573],"study_design_scores_gemma":[0.00004875867,0.0009647263,0.01603995,0.0001696614,0.0002815088,0.0005365609,0.0002304557,0.005032985,0.9404129,0.0007039377,0.0354702,0.0001083799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3786471,0.01163185,0.5656205,0.0006492283,0.001301757,0.003601331,0.01594828,0.00459426,0.01800575],"genre_scores_gemma":[0.2368299,0.006247588,0.7048716,0.001272368,0.000287337,0.01248343,0.02068579,0.001991118,0.01533083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003993998,"threshold_uncertainty_score":0.01755857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008757577955856638,"score_gpt":0.2532434487052105,"score_spread":0.2444858707493539,"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."}}