{"id":"W4243579099","doi":"10.1515/iupac.85.0584","title":"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":"Chemical nomenclature; Terminology; Mass spectrometry; Chemistry; Standardization; Analytical Chemistry (journal); Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002182403,0.0005393025,0.0006376052,0.0002307663,0.000116777,0.00008471312,0.0008637093,0.0005750108,0.1986154],"category_scores_gemma":[0.0001409459,0.0004222859,0.0002934462,0.0002458223,0.0001244689,0.00005743514,0.0001831547,0.0007282899,0.00001063781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006979026,"about_ca_system_score_gemma":0.0002933193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005031126,"about_ca_topic_score_gemma":0.00006248039,"domain_scores_codex":[0.9972078,0.00001625513,0.0005231641,0.0007249481,0.0009483676,0.0005794771],"domain_scores_gemma":[0.9974168,0.00008321749,0.0003271184,0.001740015,0.0002281826,0.0002046942],"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":[0.00002937127,0.0001500211,0.000003650459,0.0001753652,0.0000926462,0.00003152197,8.819054e-7,2.20195e-8,0.002096973,0.0003196426,0.9955252,0.001574695],"study_design_scores_gemma":[0.0003652859,0.00005825971,9.878445e-7,0.0002115988,0.0001074771,0.00001896511,0.000004760825,0.0000014742,0.00269578,0.005663011,0.990328,0.0005444289],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001875487,0.0002327541,0.0005135064,0.0007788675,0.0001094675,0.0001385006,0.9901507,0.0003216231,0.007735801],"genre_scores_gemma":[0.00004456136,0.00130617,0.0009528333,0.0001298792,0.001465814,0.00008863712,0.9918147,0.00007115165,0.004126274],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1986048,"threshold_uncertainty_score":0.9998229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155301112094633,"score_gpt":0.3754391130533654,"score_spread":0.363886101932419,"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."}}