{"id":"W4235182312","doi":"10.1515/iupac.85.0726","title":"Sector Mass Spectrometer","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":"Terminology; Chemical nomenclature; Mass spectrometry; Chemistry; Standardization; Accelerator mass spectrometry; Analytical Chemistry (journal); Political science; Chromatography; Law; Linguistics","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":[0.002053188,0.002035118,0.001737345,0.005128031,0.001131618,0.004217746,0.003299291,0.001682574,0.1297086],"category_scores_gemma":[0.00907502,0.0005916717,0.001439523,0.01026788,0.0004341992,0.003835009,0.002599251,0.00189286,0.3024749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001847145,"about_ca_system_score_gemma":0.003315377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01016704,"about_ca_topic_score_gemma":0.01283803,"domain_scores_codex":[0.9971932,0.0003654823,0.0004191928,0.0008048486,0.0009567754,0.0002605083],"domain_scores_gemma":[0.9958791,0.0006795252,0.0005231176,0.0009760222,0.001751944,0.0001903631],"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":[0.0001050323,0.00001302569,0.0006606137,0.0009463333,0.00003744302,0.00001847003,0.00002127543,0.0001273493,0.0002485947,0.0009836721,0.9866355,0.0102026],"study_design_scores_gemma":[0.00005847231,0.000007714478,0.001377046,0.0002329234,0.00001894695,0.00004044434,0.00003626908,0.0001336294,0.0004272325,0.001683564,0.9959661,0.00001778072],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001080002,0.0002565446,0.0003791028,0.0001379825,0.00005234725,0.00002545682,0.9942114,0.001514101,0.003314948],"genre_scores_gemma":[0.000442379,0.0004339805,0.001217712,0.0001879425,0.00002345302,0.00009859759,0.9946337,0.00037611,0.002586163],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1297086,"threshold_uncertainty_score":0.4339184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01306310854237504,"score_gpt":0.3680149162489084,"score_spread":0.3549518077065333,"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."}}