{"id":"W4251152131","doi":"10.1515/iupac.85.0624","title":"Negative Ion Chemical Ionization (NICI)","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; Accelerator mass spectrometry; European commission; Analytical Chemistry (journal); Environmental chemistry; Chromatography; Business; Organic chemistry; European union","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":[0.003467633,0.00215555,0.002051242,0.006385797,0.001213915,0.004762829,0.003450413,0.001511219,0.1086807],"category_scores_gemma":[0.01770936,0.0006922731,0.001753365,0.01235916,0.0005634208,0.003662807,0.00303814,0.002250757,0.1794689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00203703,"about_ca_system_score_gemma":0.004739436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00976156,"about_ca_topic_score_gemma":0.01400994,"domain_scores_codex":[0.9952115,0.0007438524,0.000784229,0.001280184,0.001649118,0.0003312297],"domain_scores_gemma":[0.9926797,0.001858309,0.001162519,0.001765577,0.002266515,0.0002673546],"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":[0.0001270692,0.00001518945,0.001123461,0.002339603,0.00008261407,0.00002699904,0.00002423347,0.0001409543,0.000341253,0.0009143354,0.9808477,0.01401664],"study_design_scores_gemma":[0.00006463834,0.0000108218,0.002318064,0.000500715,0.00004783769,0.00006941305,0.0000310435,0.0001271965,0.0005992166,0.001867516,0.994337,0.00002653564],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001366625,0.0006305028,0.000551183,0.0001320065,0.00007918605,0.00005157627,0.9939749,0.001113169,0.003330854],"genre_scores_gemma":[0.0005687665,0.0007458153,0.00176064,0.0002391001,0.00002581567,0.0002411009,0.9940977,0.0003393614,0.001981751],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1086807,"threshold_uncertainty_score":0.363573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089022866921396,"score_gpt":0.3720454780489818,"score_spread":0.3611552493797678,"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."}}