{"id":"W3211728852","doi":"10.1093/nar/gkab1052","title":"NP-MRD: the Natural Products Magnetic Resonance Database","year":2021,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Center for Complementary and Integrative Health; Canada Foundation for Innovation; Genome Canada; Office of Dietary Supplements","keywords":"Natural product; Nuclear magnetic resonance spectroscopy; NMR spectra database; Database; Proton NMR; Computer science; Information retrieval; Nuclear magnetic resonance; Chemistry; Spectral line; Physics; Stereochemistry","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":[0.001000894,0.0001439991,0.0001540196,0.00005931485,0.0004074387,0.00008551878,0.000502092,0.00007793049,0.0001293247],"category_scores_gemma":[0.001565184,0.00010262,0.0000619791,0.0006423461,0.0003521801,0.000005564204,0.0009554813,0.0004652789,0.00008624561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002067953,"about_ca_system_score_gemma":0.0002184395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002203023,"about_ca_topic_score_gemma":0.0000559275,"domain_scores_codex":[0.9978171,0.0003086474,0.0001714207,0.0006120748,0.000511713,0.0005790338],"domain_scores_gemma":[0.9982089,0.00005509603,0.00002576483,0.001071387,0.0005717487,0.00006707991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006651282,0.00006792934,0.0009551085,0.00002432824,0.00002798591,0.00003304149,0.00004998921,2.727093e-7,0.9026878,0.002305493,0.08399549,0.009786043],"study_design_scores_gemma":[0.0002910052,0.0001299001,0.007101643,0.000007738436,0.000006971276,0.00003995847,0.0001978162,0.0000203045,0.237795,0.0001722819,0.754109,0.0001284845],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8677716,0.1121459,0.00002032387,0.008792146,0.0004357689,0.0003463479,0.00005872186,0.00001713304,0.01041208],"genre_scores_gemma":[0.9664032,0.007577846,0.001649513,0.0004884275,0.0007283056,0.00005305207,0.0001049844,0.00003329896,0.02296131],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6701134,"threshold_uncertainty_score":0.4184721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03154164720562923,"score_gpt":0.3215847733951467,"score_spread":0.2900431261895175,"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."}}