{"id":"W2950873602","doi":"10.1039/c9ja00017h","title":"Accurate modelling of small-scale linear ion trap operating mode using He buffer gas to improve sensitivity and resolution for in-the-field mass spectrometry","year":2019,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep de Saint Jerome","funders":"FP7 Security; European Commission","keywords":"Resolution (logic); Sensitivity (control systems); Trap (plumbing); Buffer gas; Ion trap; Mass spectrometry; Analytical Chemistry (journal); Chemistry; Scale (ratio); Ion; Chromatography; Environmental science; Physics; Computer science; Optics","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":[],"consensus_categories":[],"category_scores_codex":[0.001223756,0.0002503571,0.0006704133,0.0005690949,0.00008518079,0.00007117027,0.0002826942,0.0002078028,0.0001628474],"category_scores_gemma":[0.0002163128,0.0002034074,0.0002831259,0.0008935648,0.00004445166,0.0001649655,0.0000665757,0.0007122027,0.000001672539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002763756,"about_ca_system_score_gemma":0.00008579548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009611313,"about_ca_topic_score_gemma":0.00001332075,"domain_scores_codex":[0.9978009,0.00005673438,0.0009403316,0.000372238,0.0003830295,0.0004467044],"domain_scores_gemma":[0.9980395,0.0007969806,0.0004400635,0.0003773628,0.0001902329,0.0001558423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002620448,0.0001988972,0.002645862,0.0001870662,0.0001054284,0.00001130292,0.00009597798,0.008581496,0.9839343,0.003711705,0.00005926958,0.00020662],"study_design_scores_gemma":[0.0006433869,0.0003564177,0.0001908664,0.0001411778,0.0001325108,0.0001056482,0.0003009701,0.6996762,0.2948753,0.003314804,0.00004623835,0.0002165215],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6895742,0.00005812842,0.3086755,0.0008420111,0.00003269581,0.0001990447,0.00001820781,0.00001191593,0.0005883145],"genre_scores_gemma":[0.8762849,0.00006293341,0.1231218,0.0001180029,0.0003186143,0.000004459474,0.00000296133,0.00002747775,0.00005883696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6910947,"threshold_uncertainty_score":0.8294713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02727116796233721,"score_gpt":0.3033980981449916,"score_spread":0.2761269301826544,"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."}}