{"id":"W4255329673","doi":"10.1515/iupac.70.0007","title":"NMR Data Acquisition, Processing, and Referencing","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"NMR spectroscopy and applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Chemical nomenclature; Field (mathematics); Computer science; Task (project management); Data science; Information retrieval; Chemistry; Engineering; Mathematics; Systems engineering","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":[0.01354315,0.002138597,0.002054211,0.006543969,0.001341843,0.00465919,0.005361661,0.002377562,0.07317308],"category_scores_gemma":[0.04993287,0.001173996,0.001309689,0.01015194,0.00108594,0.003277224,0.004160438,0.004382307,0.158645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002123882,"about_ca_system_score_gemma":0.009430814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007897115,"about_ca_topic_score_gemma":0.01276792,"domain_scores_codex":[0.9917257,0.001786977,0.002374095,0.001849621,0.001662348,0.0006011795],"domain_scores_gemma":[0.9748507,0.005075175,0.002697397,0.009819268,0.006194637,0.001362843],"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":[0.0000924688,0.0000178887,0.001005359,0.0009754031,0.00003017284,0.00002461168,0.00004512578,0.0001089804,0.0002565043,0.0007804862,0.9899136,0.006749548],"study_design_scores_gemma":[0.0001846476,0.00001316892,0.001823697,0.000637134,0.00003188361,0.00006538617,0.00007271102,0.0002128638,0.0009385048,0.002348362,0.9936335,0.00003812833],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001928356,0.0001253726,0.00156944,0.0003305871,0.0001534708,0.0001972906,0.9940047,0.001582162,0.001844201],"genre_scores_gemma":[0.000542259,0.0001166062,0.00401978,0.0002253123,0.00002354552,0.000905101,0.992882,0.0003010268,0.0009843612],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07317308,"threshold_uncertainty_score":0.2447883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02059161823795412,"score_gpt":0.4473679906601842,"score_spread":0.42677637242223,"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."}}