{"id":"W2027994854","doi":"10.1186/1471-2164-14-33","title":"Comparative gene expression between two yeast species","year":2013,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Human Genome Research Institute; Canadian Institutes of Health Research; Princeton University; National Institutes of Health; National Science Foundation","keywords":"Biology; DNA microarray; Saccharomyces cerevisiae; Gene expression; Computational biology; Gene; Expression (computer science); Genetics; Gene expression profiling; Comparative genomics; Conserved sequence; Evolutionary biology; Regulation of gene expression; Divergence (linguistics); Functional genomics; Genomics; Function (biology); Genome; Peptide sequence; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000794988,0.0002752597,0.0004712802,0.00149675,0.0004356048,0.0006046463,0.0004981466,0.000343486,0.00120602],"category_scores_gemma":[0.001926265,0.0001731148,0.0004693569,0.001976656,0.0004628656,0.0004498194,0.00076937,0.0003996788,0.0002890528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006142664,"about_ca_system_score_gemma":0.0003798608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099384,"about_ca_topic_score_gemma":0.001541447,"domain_scores_codex":[0.9991072,0.0001266408,0.00006388286,0.0004403382,0.0002022124,0.0000597798],"domain_scores_gemma":[0.99886,0.0004353123,0.0002408397,0.0001782446,0.0002071435,0.00007842115],"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":[0.0013056,0.0001425591,0.09648805,0.001021867,0.0003769039,0.00034846,0.0007877281,0.00385737,0.8508065,0.002751629,0.0007987104,0.04131453],"study_design_scores_gemma":[0.00008930198,0.001173851,0.6191056,0.0001919591,0.0006684682,0.002175255,0.001571391,0.02618895,0.3019771,0.01189508,0.03484559,0.0001174431],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643004,0.001255186,0.02518856,0.00009510936,0.0000361534,0.00005856981,0.006735577,0.0003150011,0.002015427],"genre_scores_gemma":[0.949169,0.0006014123,0.03371813,0.0001150972,0.00001801437,0.0001163163,0.0158216,0.00009414915,0.0003463644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00149675,"threshold_uncertainty_score":0.004456878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805148357991946,"score_gpt":0.2520235917047667,"score_spread":0.2239721081248472,"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."}}