{"id":"W4240609839","doi":"10.1515/iupac.85.0388","title":"Continuous Dynode Particle Multiplier","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","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; Analytical Chemistry (journal); Chromatography; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001186235,0.002098337,0.001438402,0.002276158,0.0008037274,0.002442112,0.0034897,0.001522066,0.06521827],"category_scores_gemma":[0.008660448,0.0005785109,0.001703113,0.004408939,0.0003137205,0.00178325,0.001514596,0.001935397,0.09689983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001439904,"about_ca_system_score_gemma":0.002674977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01231042,"about_ca_topic_score_gemma":0.01950401,"domain_scores_codex":[0.9986206,0.0002496779,0.0001840377,0.0003685721,0.0004265075,0.0001505258],"domain_scores_gemma":[0.9978164,0.0006347032,0.0001963561,0.0006525432,0.000596201,0.0001037524],"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":[0.0001561114,0.00004911297,0.0009879903,0.0007862131,0.0000454822,0.00002594155,0.00001292854,0.002058389,0.000133715,0.001316768,0.9734178,0.02100959],"study_design_scores_gemma":[0.0003428401,0.00005399037,0.00255443,0.0004412045,0.00004450318,0.0001474043,0.00006073394,0.007012169,0.001073548,0.007284482,0.98094,0.00004470311],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006035301,0.000547507,0.002045485,0.0002216016,0.000137043,0.00007884533,0.9909531,0.002414855,0.00299817],"genre_scores_gemma":[0.001810842,0.0004567033,0.004067573,0.0001318566,0.00002388025,0.0003236476,0.9906608,0.000239617,0.002285047],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06521827,"threshold_uncertainty_score":0.2181768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987011709467422,"score_gpt":0.406095205570549,"score_spread":0.3862250884758747,"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."}}