{"id":"W91916607","doi":"10.1007/978-1-4939-2269-7_23","title":"Chemical Genomic Profiling via Barcode Sequencing to Predict Compound Mode of Action","year":2014,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Occupational Cancer Research Centre; University of Toronto","funders":"National Institute of General Medical Sciences; National Human Genome Research Institute; Canadian Institutes of Health Research","keywords":"Barcode; Profiling (computer programming); Computational biology; Mode of action; Genomics; Saccharomyces cerevisiae; DNA sequencing; Computer science; Biology; Genetics; DNA; Gene; Genome; Biochemistry","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":[0.0002992994,0.0007754882,0.0006007479,0.001261359,0.0002492546,0.0007134587,0.0003430643,0.0005858419,0.001785391],"category_scores_gemma":[0.00104798,0.0002909862,0.0007259225,0.001187339,0.0003558492,0.0004917125,0.0004045573,0.0009743324,0.00145303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005534638,"about_ca_system_score_gemma":0.000996705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002106421,"about_ca_topic_score_gemma":0.004081699,"domain_scores_codex":[0.9995133,0.00004964586,0.00002044861,0.0000991644,0.0002571383,0.00006033514],"domain_scores_gemma":[0.999338,0.0001919405,0.0001403321,0.00005977012,0.0002084062,0.00006160277],"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":[0.0001589517,0.00007134337,0.001570892,0.00009352794,0.00002170691,0.00004426428,0.00001817212,0.0006480156,0.9862565,0.0002441515,0.0001421008,0.0107303],"study_design_scores_gemma":[0.0000141165,0.0004626068,0.008197471,0.00002147553,0.0000718979,0.0001650482,0.00005092047,0.00707364,0.9802214,0.0004334506,0.003261607,0.00002637341],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8020901,0.004627078,0.143648,0.0009158466,0.0001939227,0.0007792981,0.03247802,0.00202236,0.01324539],"genre_scores_gemma":[0.8484963,0.004321923,0.1235413,0.0005659508,0.00007776272,0.0003368513,0.01679255,0.00021845,0.005648975],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002106421,"threshold_uncertainty_score":0.005972743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03406619873020545,"score_gpt":0.3828063933750657,"score_spread":0.3487401946448602,"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."}}