{"id":"W10925699","doi":"","title":"Yeast genomics and proteomics in drug discovery and target validation.","year":2003,"lang":"en","type":"article","venue":"PubMed","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Drug discovery; Computational biology; Proteomics; Saccharomyces cerevisiae; Budding yeast; Yeast; Identification (biology); Genomics; Chemical genetics; Functional genomics; Drug development; Biology; Drug target; Bioinformatics; Drug; Genetics; Genome; Biochemistry; Small molecule; Gene; Pharmacology","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":[0.0040813,0.000871017,0.001365824,0.002227145,0.000392272,0.001557016,0.0007356545,0.0009011131,0.00182022],"category_scores_gemma":[0.002700476,0.0003552653,0.0005596437,0.003170828,0.001291233,0.001596557,0.001071111,0.001134278,0.002087679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001428191,"about_ca_system_score_gemma":0.001697604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002231591,"about_ca_topic_score_gemma":0.00209694,"domain_scores_codex":[0.9986993,0.0007108907,0.00007136619,0.000131329,0.0003310552,0.00005605347],"domain_scores_gemma":[0.9987808,0.0006625096,0.0001395018,0.0001015199,0.0002086945,0.0001068735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008356471,0.0001386399,0.003468719,0.005051754,0.0003376145,0.0008458434,0.0001963923,0.009905742,0.02758427,0.1601603,0.05810257,0.7333725],"study_design_scores_gemma":[0.0001904518,0.000326698,0.006367887,0.001230694,0.0002698812,0.002385847,0.0003934256,0.02337476,0.03415048,0.301569,0.6296317,0.0001091232],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.01702696,0.525061,0.394375,0.02947028,0.002448361,0.0003477828,0.003845364,0.004444357,0.02298097],"genre_scores_gemma":[0.1747589,0.4621812,0.3408648,0.00749439,0.001261885,0.0005051961,0.004791062,0.0003123702,0.007830221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0040813,"threshold_uncertainty_score":0.02158421,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005895093471814216,"score_gpt":0.1767366164631365,"score_spread":0.1708415229913222,"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."}}