{"id":"W2253716040","doi":"10.1038/ncomms9421","title":"An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Waterloo; McMaster University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Joint Programming Initiative on Antimicrobial Resistance","keywords":"Genome; Computational biology; Natural product; Nonribosomal peptide; Identification (biology); Biology; Modular design; Drug discovery; Computer science; Genetics; Bioinformatics; Gene; Biosynthesis; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008051014,0.0002850915,0.0004332954,0.0001784125,0.0003237012,0.00007998651,0.001499222,0.0002482854,0.000001903112],"category_scores_gemma":[0.002630383,0.0001703139,0.0001231982,0.001044831,0.0002606894,0.0004733105,0.0003349333,0.001121739,0.000009595311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00014663,"about_ca_system_score_gemma":0.0004053266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004372527,"about_ca_topic_score_gemma":0.0001040864,"domain_scores_codex":[0.9982258,0.00009094562,0.0004514241,0.0004888813,0.0003747097,0.0003682364],"domain_scores_gemma":[0.9939155,0.0002455496,0.0002205805,0.003739571,0.001758079,0.0001207275],"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":[0.0008101448,0.0006937991,0.0002240066,0.0002217425,0.000357123,0.000001992762,0.001249289,0.00003650835,0.908578,0.003833449,0.07538418,0.008609775],"study_design_scores_gemma":[0.00256075,0.0008690583,0.02050589,0.0002847724,0.0008567108,0.0001738997,0.0009543383,0.01734783,0.5805508,0.000243411,0.3747328,0.0009197065],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7410203,0.09214426,0.00003479762,0.1562421,0.002425915,0.006756586,0.0003785972,0.0006928963,0.0003045606],"genre_scores_gemma":[0.9750195,0.0002673043,0.02139361,0.001159029,0.0004950638,0.00002961498,0.0006653713,0.00004742546,0.0009231226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3280271,"threshold_uncertainty_score":0.6945201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04220684354348562,"score_gpt":0.3280625440542513,"score_spread":0.2858557005107656,"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."}}