{"id":"W4245261344","doi":"10.1515/iupac.85.0401","title":"Daly Detector","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Analytical Chemistry and Chromatography","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; Standardization; Accelerator mass spectrometry; Chemistry; Tandem mass spectrometry; Analytical Chemistry (journal); Computer science; Environmental chemistry; Chromatography; 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":[0.00195003,0.002141823,0.00239267,0.004431602,0.001391466,0.00469442,0.004110327,0.001708368,0.1761522],"category_scores_gemma":[0.00854711,0.0008918786,0.001814739,0.008697914,0.0004127629,0.003958253,0.002178819,0.002328673,0.2925901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001974555,"about_ca_system_score_gemma":0.003571668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01200346,"about_ca_topic_score_gemma":0.01810525,"domain_scores_codex":[0.9972652,0.0003090104,0.0003067752,0.0008146238,0.001036218,0.0002682241],"domain_scores_gemma":[0.9970978,0.0004820672,0.0003018789,0.0007495076,0.001239662,0.0001290633],"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":[0.0001354105,0.00001778864,0.00077474,0.0007658848,0.00004481875,0.00001584105,0.00001886588,0.0002238456,0.0002903127,0.001418738,0.9855827,0.010711],"study_design_scores_gemma":[0.00005947509,0.00000844134,0.0009127378,0.0001164365,0.0000259866,0.00003532446,0.00002592445,0.0003208481,0.0007948615,0.002089656,0.9955902,0.00002015889],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002298456,0.0004756529,0.001048877,0.0001895645,0.000127279,0.00004221744,0.9853461,0.004159732,0.008380826],"genre_scores_gemma":[0.0008486459,0.0005549354,0.002897557,0.0002191065,0.00002996292,0.0001308136,0.9894667,0.0008679933,0.004984236],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1761522,"threshold_uncertainty_score":0.5892878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009532179748770415,"score_gpt":0.3557092345078465,"score_spread":0.3461770547590761,"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."}}