{"id":"W1978123613","doi":"10.1016/j.chroma.2012.01.046","title":"Development of a hydrophilic interaction liquid chromatography–mass spectrometry method for detection and quantification of urea thermal decomposition by-products in emission from diesel engine employing selective catalytic reduction technology","year":2012,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Chemistry; Chromatography; Ammonium formate; Cyanuric acid; Hydrophilic interaction chromatography; Melamine; Electrospray ionization; Selective catalytic reduction; Detection limit; Mass spectrometry; Analyte; Solid phase extraction; High-performance liquid chromatography; Catalysis; 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":[0.0008143473,0.0008572511,0.0006046345,0.0006956948,0.0004678776,0.0004756647,0.001046674,0.001136931,0.0005337503],"category_scores_gemma":[0.0006140458,0.0006504426,0.0005458224,0.0002967522,0.000464175,0.0007350714,0.0005552648,0.001183312,0.0006318492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003700365,"about_ca_system_score_gemma":0.0009597135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019173,"about_ca_topic_score_gemma":0.003110265,"domain_scores_codex":[0.9992871,0.00007953907,0.00004192158,0.0001637542,0.0003842124,0.00004357882],"domain_scores_gemma":[0.9996282,0.0000924913,0.0000546581,0.000028897,0.0001499273,0.00004580512],"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":[0.00002830871,0.00004530692,0.0001968533,0.00004170777,0.000009783275,0.00003715255,0.00001029274,0.00003991011,0.9939242,0.00008372506,0.0000499219,0.00553269],"study_design_scores_gemma":[0.00001108475,0.0002008356,0.001293758,0.000004010738,0.00002206872,0.0003730611,0.000009231338,0.00268376,0.9935688,0.00004485721,0.001769577,0.00001900067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3850314,0.004731861,0.6029676,0.0004712598,0.0002783497,0.0006440535,0.0005522984,0.001735012,0.00358814],"genre_scores_gemma":[0.5702975,0.003278027,0.416886,0.0005556255,0.0001067264,0.0005484601,0.001178074,0.0001377238,0.007011861],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001136931,"threshold_uncertainty_score":0.004306734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01336081286676894,"score_gpt":0.2934703971503861,"score_spread":0.2801095842836172,"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."}}