{"id":"W4391891200","doi":"10.1039/d3an02109b","title":"Liquid electron ionization-mass spectrometry as a novel strategy for integrating normal-phase liquid chromatography with low and high-resolution mass spectrometry","year":2024,"lang":"en","type":"article","venue":"The Analyst","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University","funders":"","keywords":"Mass spectrometry; Chemistry; Chromatography; Direct electron ionization liquid chromatography–mass spectrometry interface; Resolution (logic); Analyte; Atmospheric-pressure chemical ionization; Analytical Chemistry (journal); Electron ionization; Electrospray ionization; Ionization; Electrospray; Ambient ionization; Chemical ionization; Ion","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"],"consensus_categories":[],"category_scores_codex":[0.0003154603,0.0004778486,0.0004806621,0.0003556867,0.0004130414,0.0003369508,0.0003917706,0.0002280555,0.0005531249],"category_scores_gemma":[0.00005985574,0.0003406846,0.0003382358,0.002220802,0.0003587676,0.0002893386,0.00004620084,0.0005719914,0.00001359515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001172637,"about_ca_system_score_gemma":0.0001556278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009243477,"about_ca_topic_score_gemma":0.0000261589,"domain_scores_codex":[0.9976226,0.0000259943,0.0005221347,0.0007170941,0.0004247161,0.0006874375],"domain_scores_gemma":[0.9986379,0.0002827134,0.0001867864,0.0005354144,0.000142728,0.0002144856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009132141,0.0002074547,0.00008447367,0.0007781941,0.001175278,0.00003497999,0.00009895358,0.0002287283,0.979105,0.01716483,0.0001666557,0.00004224126],"study_design_scores_gemma":[0.001762452,0.001938971,0.0000261011,0.000656758,0.001336718,0.0001662716,0.001562872,0.02615591,0.9623839,0.002612122,0.0005321669,0.0008657812],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8228876,0.001792002,0.1680997,0.0004262216,0.00003564189,0.0001835579,0.0001252257,0.000313124,0.006136955],"genre_scores_gemma":[0.9958147,0.0001657184,0.002599143,0.00006876433,0.00047991,0.00005814803,0.0003269624,0.00007466246,0.0004119414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1729272,"threshold_uncertainty_score":0.9999045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007439016856792265,"score_gpt":0.2531163428319303,"score_spread":0.245677325975138,"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."}}