{"id":"W4365142227","doi":"10.1515/iupac.94.0332","title":"Chemical Shift (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); Epistemology; Computer science; Chemistry; Linguistics; Philosophy; Mathematics; Political science; Law","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":[0.001359319,0.003397681,0.002279185,0.003866272,0.001324037,0.00221946,0.003162212,0.001946306,0.1246331],"category_scores_gemma":[0.005250338,0.0008334157,0.00137752,0.006634884,0.000567656,0.002477992,0.002079824,0.002389197,0.2509595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001305783,"about_ca_system_score_gemma":0.001461531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01234511,"about_ca_topic_score_gemma":0.0268831,"domain_scores_codex":[0.9985476,0.0002199392,0.000179107,0.0005712196,0.0003412624,0.0001407261],"domain_scores_gemma":[0.9976543,0.0004545806,0.0002962996,0.0008515137,0.0006141379,0.0001292773],"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":[0.0001876648,0.00004554247,0.0005840717,0.001450068,0.00004359878,0.00003634344,0.00003049368,0.0002669341,0.002107703,0.0004932692,0.9849315,0.009822701],"study_design_scores_gemma":[0.0001716392,0.00006328968,0.004791226,0.0002958461,0.00005860136,0.0002411983,0.00007883434,0.0004888698,0.002154252,0.002926505,0.9886327,0.0000969616],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003419659,0.0004798449,0.0006321126,0.00008082295,0.00009746795,0.00002520527,0.9940504,0.001700202,0.002591973],"genre_scores_gemma":[0.000521887,0.0002754674,0.001173817,0.0001233361,0.00002219254,0.00008431822,0.9963762,0.0002011031,0.001221527],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1246331,"threshold_uncertainty_score":0.4169391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221358859821705,"score_gpt":0.417385878688782,"score_spread":0.3951722900905649,"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."}}