{"id":"W2082214848","doi":"10.1002/mrd.21364","title":"Combining resources to obtain a comprehensive survey of the bovine embryo transcriptome through deep sequencing and microarrays","year":2011,"lang":"en","type":"article","venue":"Molecular Reproduction and Development","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; Procter & Gamble (Canada); Hôtel-Dieu de Québec; University of Alberta; Université Laval","funders":"","keywords":"Biology; Bovine genome; Genetics; Microarray; Indel; Genome; Computational biology; DNA microarray; Gene chip analysis; Embryo; Microarray analysis techniques; Transcriptome; Gene; Single-nucleotide polymorphism; 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":[0.001566413,0.0007174665,0.001079446,0.001362107,0.0006909881,0.001049073,0.000623067,0.0005110623,0.002789796],"category_scores_gemma":[0.001162224,0.0004835273,0.0008760752,0.001605517,0.0001950594,0.0006657499,0.001306863,0.001043348,0.001912263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000547104,"about_ca_system_score_gemma":0.001046885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002075608,"about_ca_topic_score_gemma":0.00725717,"domain_scores_codex":[0.9987889,0.0002036115,0.0001012555,0.0004181176,0.0003558546,0.0001323162],"domain_scores_gemma":[0.9992674,0.0001893287,0.00008523555,0.0001321526,0.0002417808,0.00008396957],"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":[0.0001941024,0.00004876651,0.002731903,0.0005421336,0.0000662828,0.00009272084,0.0001589879,0.001335858,0.9477278,0.0009066012,0.00298462,0.04321019],"study_design_scores_gemma":[0.0002160181,0.001043366,0.1050228,0.0004910329,0.0005412497,0.001113616,0.0005556098,0.02843051,0.5830813,0.005966246,0.2733115,0.0002267898],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2734762,0.008991532,0.6251098,0.001201325,0.0004463184,0.001019222,0.06817642,0.006599396,0.01497976],"genre_scores_gemma":[0.1212146,0.003787151,0.7373201,0.001147591,0.0001333171,0.001925295,0.1276217,0.0009483257,0.005902054],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002789796,"threshold_uncertainty_score":0.009332776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04395246322848861,"score_gpt":0.262392888433828,"score_spread":0.2184404252053394,"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."}}