{"id":"W4404642680","doi":"10.1093/nar/gkae1067","title":"The Natural Products Magnetic Resonance Database (NP-MRD) for 2025","year":2024,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Alberta","funders":"National Center for Complementary and Integrative Health; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canada Foundation for Innovation; Office of Dietary Supplements","keywords":"Database; Spectral line; Raw data; NMR spectra database; Computer science; Nuclear magnetic resonance; Biology; Physics","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":[0.004008853,0.001361893,0.001749619,0.004903337,0.0008295936,0.004481569,0.002879669,0.002054813,0.08833167],"category_scores_gemma":[0.01038506,0.0007755251,0.001191385,0.006351386,0.0004303626,0.004794894,0.003318446,0.001691425,0.09863991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001756715,"about_ca_system_score_gemma":0.005511477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008611789,"about_ca_topic_score_gemma":0.01113747,"domain_scores_codex":[0.9982386,0.0002267667,0.0002371629,0.0002717289,0.0008070919,0.0002187011],"domain_scores_gemma":[0.9957842,0.0005545558,0.0005486816,0.0006447578,0.001580146,0.0008876173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007019207,0.00007504141,0.001209982,0.001941362,0.00007946919,0.0001310622,0.00005786023,0.000290398,0.0019614,0.003932138,0.9249693,0.06465013],"study_design_scores_gemma":[0.0001068472,0.0000445057,0.001471963,0.0002504185,0.00004276901,0.00006522205,0.00002962076,0.0003757198,0.0009155308,0.001849153,0.9948136,0.00003464723],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001947418,0.005263248,0.004809952,0.002848073,0.0005903689,0.0002180369,0.9445489,0.01154366,0.02823028],"genre_scores_gemma":[0.003481265,0.003383693,0.01030576,0.001440506,0.0001279707,0.0001827003,0.973656,0.0009860592,0.006436056],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08833167,"threshold_uncertainty_score":0.2954988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03458569881504392,"score_gpt":0.3485999667836209,"score_spread":0.314014267968577,"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."}}