{"id":"W4254109856","doi":"10.1515/iupac.85.0312","title":"After Mass Analysis","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Research Council Canada","funders":"","keywords":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Standardization; Accelerator mass spectrometry; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; Linguistics; Organic chemistry","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":[0.002423304,0.002484524,0.002075245,0.005846237,0.001163905,0.005514844,0.002617972,0.001870066,0.169285],"category_scores_gemma":[0.01567784,0.0007310651,0.002372044,0.008709972,0.0005141998,0.004226788,0.002862636,0.002475251,0.3111759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001822942,"about_ca_system_score_gemma":0.003911209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01174648,"about_ca_topic_score_gemma":0.01767407,"domain_scores_codex":[0.9966215,0.0004016744,0.0006056089,0.001059132,0.001022717,0.0002894201],"domain_scores_gemma":[0.992878,0.001536459,0.000825616,0.002149013,0.002348941,0.0002619897],"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":[0.00009437696,0.00001407665,0.001125859,0.001309168,0.00005689681,0.00002591086,0.00001864442,0.0001223637,0.0002139253,0.0008556465,0.980198,0.0159651],"study_design_scores_gemma":[0.00004483463,0.000008676103,0.00188314,0.0003721126,0.00003053144,0.00006112688,0.00003557039,0.000111624,0.0003793124,0.001827518,0.9952238,0.00002180715],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000151842,0.0005249784,0.0006031814,0.0002344904,0.0001461019,0.00004568259,0.9924076,0.001702231,0.004183937],"genre_scores_gemma":[0.0007246305,0.0006674116,0.002226261,0.0003483262,0.00004769355,0.0001572206,0.9909449,0.0004739511,0.004409616],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.169285,"threshold_uncertainty_score":0.5663148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008003674401071527,"score_gpt":0.3729976929312794,"score_spread":0.3649940185302079,"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."}}