{"id":"W2229450847","doi":"10.1093/nar/gkv1012","title":"Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM)","year":2015,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Microbial Natural Products and Biosynthesis","field":"Medicine","cited_by":274,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Joint Programming Initiative on Antimicrobial Resistance","keywords":"Biology; Computational biology; Natural product; Genome; Metagenomics; Cheminformatics; Prism; Genomics; Drug discovery; Identification (biology); Gene; Bioinformatics; Genetics; 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":[0.001131076,0.001872186,0.0006746591,0.001515066,0.000586792,0.00141505,0.001437737,0.0008135263,0.01152696],"category_scores_gemma":[0.003147666,0.0007330089,0.002334768,0.001739155,0.0004137844,0.001489187,0.002587696,0.001475236,0.005802865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006383297,"about_ca_system_score_gemma":0.002067757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001897538,"about_ca_topic_score_gemma":0.002856218,"domain_scores_codex":[0.9995653,0.00008815235,0.00003892063,0.0001790397,0.00008584907,0.00004269202],"domain_scores_gemma":[0.9993708,0.000255317,0.00009165747,0.000128736,0.00007715978,0.00007645301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006353111,0.0007276771,0.02516506,0.007827513,0.001196807,0.001576017,0.001157625,0.09152862,0.09569941,0.04304501,0.3644285,0.3612947],"study_design_scores_gemma":[0.0008489707,0.0006708342,0.01448542,0.0004914178,0.0004799627,0.001109716,0.0003409686,0.4272989,0.07399531,0.05325853,0.4267715,0.0002483338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04766564,0.001381591,0.3819219,0.0008470539,0.0002533303,0.0005398486,0.2380093,0.3184564,0.01092485],"genre_scores_gemma":[0.1072816,0.001382154,0.5015687,0.0004874275,0.00006600846,0.0009125209,0.3763061,0.009018971,0.002976451],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01152696,"threshold_uncertainty_score":0.03856158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06553529268008816,"score_gpt":0.3391883476348865,"score_spread":0.2736530549547984,"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."}}