{"id":"W4386306196","doi":"10.1080/17460441.2023.2251400","title":"Applications of machine learning in microbial natural product drug discovery","year":2023,"lang":"en","type":"review","venue":"Expert Opinion on Drug Discovery","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Discovery Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Weston Family Foundation","keywords":"Drug discovery; Business process discovery; Chemical space; Computer science; Natural product; Process (computing); Artificial intelligence; Machine learning; Biochemical engineering; Computational biology; Data science; Biology; Bioinformatics; Engineering; Work in process","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005572009,0.0008011026,0.002511119,0.0008520082,0.0001299374,0.0001180737,0.0004974366,0.0001993841,0.00004949495],"category_scores_gemma":[0.000401705,0.0005592645,0.0009102335,0.001308857,0.0001792183,0.000415843,0.0003113183,0.001562495,0.0001403702],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003266277,"about_ca_system_score_gemma":0.0005317612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005170465,"about_ca_topic_score_gemma":0.00006956252,"domain_scores_codex":[0.9959714,0.0003169898,0.00135331,0.001325553,0.0004877345,0.0005449632],"domain_scores_gemma":[0.9977784,0.0003822221,0.0006972341,0.000953537,0.00008502971,0.000103627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003638379,0.001011547,0.00002355524,0.02365752,0.0004756445,0.00003076906,0.0004396999,0.00000726514,0.001763288,0.0003507549,0.04941991,0.9224562],"study_design_scores_gemma":[0.0004673956,0.00004642626,0.00001027103,0.02187375,0.00007612993,0.0000399097,0.00007093728,0.000005560579,0.001648827,0.000008313977,0.9751701,0.0005824271],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001506983,0.9932196,0.000004152142,0.001412147,0.00173789,0.00283964,0.0003167578,0.0001431692,0.0001759549],"genre_scores_gemma":[0.001625407,0.9698688,0.00007761182,0.0001631911,0.002111164,0.00009770701,0.002397191,0.0001741668,0.02348478],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9257501,"threshold_uncertainty_score":0.9996859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813201569267489,"score_gpt":0.3281669745174177,"score_spread":0.3000349588247428,"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."}}