{"id":"W4293173736","doi":"10.1007/s10142-022-00893-1","title":"Unrevealing functional candidate genes for bovine fertility through RNA sequencing meta-analysis and regulatory elements networks of co-expressed genes and lncRNAs","year":2022,"lang":"en","type":"review","venue":"Functional & Integrative Genomics","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Biology; Gene; Genetics; Candidate gene; Gene regulatory network; Computational biology; Regulatory sequence; Regulation of gene expression; Gene expression","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":[0.0008470365,0.0007060434,0.001121978,0.001052148,0.0001563139,0.0009132078,0.0006678461,0.0006535387,0.00176544],"category_scores_gemma":[0.0005678466,0.0002388096,0.0005046598,0.00120109,0.0003659155,0.0005981623,0.0003661472,0.0009815121,0.0006916602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006169354,"about_ca_system_score_gemma":0.001048858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00146377,"about_ca_topic_score_gemma":0.003244239,"domain_scores_codex":[0.9998362,0.00002176458,0.00001869243,0.00005676064,0.00005010088,0.0000164721],"domain_scores_gemma":[0.9996686,0.0001875458,0.00005293026,0.000009528932,0.00006321145,0.00001823461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0001696942,0.00002932269,0.001377011,0.01540687,0.0002608911,0.0003179145,0.00007595609,0.0005335869,0.01495524,0.003975099,0.009371904,0.9535264],"study_design_scores_gemma":[0.00004485749,0.0001907153,0.008321881,0.003705368,0.001192065,0.002141048,0.0001366397,0.0003579239,0.00771453,0.004228907,0.9718973,0.00006884747],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005016073,0.9978441,0.0006157055,0.0002194676,0.0001033811,0.000003758755,0.00009538024,0.00001029565,0.0006062474],"genre_scores_gemma":[0.003523117,0.9935183,0.001289389,0.0004349556,0.0001191017,0.00001043837,0.0003036361,0.000005345832,0.0007956532],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00176544,"threshold_uncertainty_score":0.005905926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032690414003976,"score_gpt":0.3476085516441548,"score_spread":0.2443395102437572,"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."}}