{"id":"W2018670043","doi":"10.1016/j.chroma.2012.06.062","title":"Ion chromatographic separation and quantitation of alkyl methylamines and ethylamines in atmospheric gas and particulate matter using preconcentration and suppressed conductivity detection","year":2012,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Odor and Emission Control Technologies","field":"Chemical Engineering","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Chemistry; Dimethylamine; Diethylamine; Chromatography; Trimethylamine; Ion chromatography; Detection limit; Methanesulfonic acid; Analytical Chemistry (journal); Alkyl; Ethylamine; Particle size; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003132933,0.0001311245,0.0002958876,0.0001364878,0.00004244832,0.00003188967,0.00002700655,0.0001269167,0.000004202428],"category_scores_gemma":[0.00008520648,0.0001104617,0.00004216444,0.0002648735,0.0001190309,0.0007595542,0.00002027613,0.0001257826,4.484618e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008840955,"about_ca_system_score_gemma":0.000005350457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003039109,"about_ca_topic_score_gemma":0.00001155169,"domain_scores_codex":[0.9991627,0.00005896596,0.0003978083,0.0001130163,0.0001174128,0.0001501023],"domain_scores_gemma":[0.9993835,0.0001231161,0.000298858,0.00006281938,0.00006603711,0.00006563697],"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":[0.00004483978,0.00002989164,0.2191859,0.000163562,0.00003641431,6.999111e-7,0.0004175294,0.00007504329,0.777994,0.00003477966,0.000002099216,0.002015189],"study_design_scores_gemma":[0.001311876,0.0001480824,0.4341041,0.000245065,0.0001188969,0.0001978931,0.0005558201,0.0376878,0.5248992,0.0005351841,0.00001679709,0.0001792911],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911543,0.005645724,0.002915021,0.00006571517,0.000080335,0.0001147618,0.000001269839,0.0000175429,0.000005317771],"genre_scores_gemma":[0.9973594,0.0006922384,0.001896797,0.000005308244,0.00003276653,0.000002419982,7.122732e-7,0.000009706583,6.263408e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2530949,"threshold_uncertainty_score":0.4504498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01695290775121665,"score_gpt":0.2718175669869235,"score_spread":0.2548646592357068,"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."}}