{"id":"W2997918501","doi":"10.1073/pnas.1901493116","title":"DeepRiPP integrates multiomics data to automate discovery of novel ribosomally synthesized natural products","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; Pfizer","keywords":"Computer science; Natural (archaeology); Computational biology; Data science; Biology","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":[0.001387525,0.0001383356,0.0003470312,0.0002078177,0.00006805286,0.00002816642,0.00127641,0.00008108409,0.000008235388],"category_scores_gemma":[0.00404592,0.00007578752,0.00007011632,0.0009703232,0.0004800699,0.0007725337,0.0004755303,0.0001975382,0.000002795584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003575597,"about_ca_system_score_gemma":0.0001012976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000157921,"about_ca_topic_score_gemma":1.594333e-7,"domain_scores_codex":[0.9979595,0.000005202154,0.0004591426,0.0004750848,0.000922098,0.0001789745],"domain_scores_gemma":[0.9986326,0.0001536229,0.0004977801,0.00004533804,0.0006385809,0.00003210188],"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":[0.0001440679,0.000118063,0.001752644,0.0002890498,0.00003709051,4.335251e-9,0.00008110895,0.000007313021,0.9932331,0.003339826,0.0005912818,0.0004064842],"study_design_scores_gemma":[0.0003143663,0.00006269833,0.0362482,0.0004986417,0.00003903834,0.00001440203,0.0001082597,0.002063866,0.9600649,0.0002894551,0.0002004545,0.00009568646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858927,0.0001628766,4.406668e-7,0.01274775,0.00007306835,0.0005918489,0.0001093659,0.00001459209,0.0004073775],"genre_scores_gemma":[0.985383,0.00002381334,0.01357718,0.0003633639,0.0000967638,9.052641e-7,0.000001497766,0.000006707302,0.000546713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03449555,"threshold_uncertainty_score":0.4843637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05890757804733093,"score_gpt":0.3148766347755096,"score_spread":0.2559690567281787,"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."}}