{"id":"W4365147223","doi":"10.1515/iupac.94.0426","title":"Dynamic Nmr","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Abandonment (legal); Meaning (existential); Field (mathematics); Computer science; Epistemology; Chemistry; Linguistics; Philosophy; Mathematics; Political science","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":[0.001266039,0.003685728,0.002023819,0.002875784,0.001718915,0.003059131,0.004478569,0.002657961,0.1180739],"category_scores_gemma":[0.004579408,0.0009044097,0.001981128,0.004018365,0.0005969864,0.002331994,0.002838188,0.00264403,0.2752857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507718,"about_ca_system_score_gemma":0.002019912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01791582,"about_ca_topic_score_gemma":0.0479838,"domain_scores_codex":[0.9985737,0.0002552567,0.0001248464,0.0005415842,0.0003076982,0.0001968566],"domain_scores_gemma":[0.9982905,0.0003317295,0.0001317342,0.0007135531,0.0003924772,0.0001400047],"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":[0.0001219353,0.00003854918,0.0004327957,0.0005840918,0.00003606124,0.00003186931,0.00001923116,0.0002917426,0.0005443605,0.000508106,0.9907584,0.006632766],"study_design_scores_gemma":[0.0001898722,0.0000434276,0.002661348,0.0003140115,0.00005373733,0.000209941,0.0000784546,0.0008796883,0.001494191,0.003326036,0.9906798,0.00006946908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002643093,0.0002819234,0.0004584138,0.0001094309,0.00008843357,0.0000267137,0.9944069,0.002042715,0.002321127],"genre_scores_gemma":[0.0003254368,0.0001165868,0.0006982828,0.0001044185,0.00001319965,0.00006497529,0.9974788,0.0001328996,0.001065484],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1180739,"threshold_uncertainty_score":0.3949965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01781572458594342,"score_gpt":0.4219333148861053,"score_spread":0.4041175903001619,"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."}}