{"id":"W4255979781","doi":"10.1515/iupac.85.0485","title":"Imaging Mass Spectrometry","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; Standardization; Tandem mass spectrometry; Analytical Chemistry (journal); Political science; Environmental chemistry; Chromatography; 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":[0.00239674,0.002057451,0.001724866,0.005977173,0.001213358,0.004386498,0.003508476,0.00206567,0.1035968],"category_scores_gemma":[0.01277309,0.0006437491,0.001664685,0.008803574,0.0004942651,0.003334722,0.002882006,0.002008273,0.1856562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002151132,"about_ca_system_score_gemma":0.003798916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01121185,"about_ca_topic_score_gemma":0.01912016,"domain_scores_codex":[0.997099,0.0004101359,0.0004305126,0.0007627122,0.001026595,0.0002709982],"domain_scores_gemma":[0.9947916,0.001065265,0.0006994911,0.001297782,0.001898,0.0002478856],"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":[0.00009855652,0.00001344248,0.0008103421,0.001633358,0.0000481853,0.00003026624,0.00002104165,0.0001229275,0.0003142412,0.0009277055,0.9813843,0.01459558],"study_design_scores_gemma":[0.00004610117,0.000007248772,0.001798163,0.0005251419,0.00003349395,0.00008644209,0.00003391803,0.0001138479,0.000543798,0.00167118,0.995119,0.00002170578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000147808,0.0008467018,0.0006735001,0.0002380249,0.00009261785,0.00004393861,0.9924977,0.001442373,0.004017383],"genre_scores_gemma":[0.0005205252,0.0008808127,0.001841997,0.0002641881,0.00002946758,0.0001362668,0.9936749,0.0002888609,0.002362938],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1035968,"threshold_uncertainty_score":0.346566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009038244680238745,"score_gpt":0.3674823805402626,"score_spread":0.3584441358600239,"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."}}