{"id":"W2046490939","doi":"10.1039/c2np20104f","title":"Using NMR to identify and characterize natural products","year":2013,"lang":"en","type":"review","venue":"Natural Product Reports","topic":"Molecular spectroscopy and chirality","field":"Chemistry","cited_by":187,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Natural (archaeology); Computational biology; Chemistry; Biology; Paleontology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007162406,0.0009295403,0.0009424938,0.002955572,0.0002771441,0.0008841863,0.0006047869,0.0008227681,0.002473282],"category_scores_gemma":[0.0005949433,0.000343456,0.0004468241,0.001930554,0.0005385467,0.001366329,0.0006425814,0.001225502,0.002994917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004326513,"about_ca_system_score_gemma":0.0005787861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008379655,"about_ca_topic_score_gemma":0.001422005,"domain_scores_codex":[0.9996852,0.00003934337,0.00002277797,0.0000680373,0.00015368,0.00003096602],"domain_scores_gemma":[0.9997815,0.00008975324,0.00003044082,0.00001128121,0.00007187817,0.00001521088],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005628611,0.0001044321,0.0003326242,0.01308669,0.00008480973,0.0004021958,0.00009371749,0.0006071591,0.05125353,0.004079071,0.009669523,0.9202299],"study_design_scores_gemma":[0.00001668008,0.0002271999,0.001364077,0.001698778,0.0001094647,0.002394656,0.0001173227,0.0003407382,0.03509622,0.002477132,0.9560976,0.00006024375],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001741481,0.9882882,0.002639688,0.0002604641,0.0002445976,0.00002308739,0.00007811889,0.00003840462,0.006685975],"genre_scores_gemma":[0.005755362,0.9891433,0.002103016,0.000207953,0.0001516865,0.00002339735,0.00009114273,0.000006013768,0.002518161],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002955572,"threshold_uncertainty_score":0.008274019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05572445987610037,"score_gpt":0.3752470080675203,"score_spread":0.31952254819142,"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."}}