{"id":"W1973141608","doi":"10.1039/b204574e","title":"Improved gas chromatography methods for micro-volume analysis of haloacetic acids in water and biological matrices","year":2002,"lang":"en","type":"article","venue":"The Analyst","topic":"Water Treatment and Disinfection","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Health Canada; U.S. Environmental Protection Agency","keywords":"Chemistry; Chromatography; Haloacetic acids; Derivatization; Gas chromatography; Detection limit; Sulfuric acid; Solid-phase microextraction; Sample preparation; Standard addition; Internal standard; Matrix (chemical analysis); Quantitative analysis (chemistry); Methanol; Gas chromatography–mass spectrometry; High-performance liquid chromatography; Mass spectrometry; Chlorine; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003263537,0.00008670514,0.0002105787,0.0001488893,0.0000639475,0.00001945398,0.00009266198,0.00004118406,0.0005768636],"category_scores_gemma":[0.000005280107,0.00004251059,0.0001521659,0.000626112,0.0001345615,0.00006240317,0.00005351696,0.00002755145,0.00001139093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001858823,"about_ca_system_score_gemma":3.019064e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006132564,"about_ca_topic_score_gemma":0.000144079,"domain_scores_codex":[0.9993542,0.000100827,0.0001652232,0.0001799665,0.00004422397,0.0001555895],"domain_scores_gemma":[0.9997215,0.00004939278,0.00004623544,0.0001530541,0.000003825869,0.00002599698],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001616831,0.00009215687,0.809725,0.000003961739,0.0002944172,3.992411e-7,0.0004908661,0.0001223779,0.1862167,0.000004161922,0.000039906,0.002993917],"study_design_scores_gemma":[0.0007938658,0.0002891102,0.8589628,0.000004411356,0.002333628,0.000003509734,0.0001953244,0.07256931,0.06268146,0.0008439028,0.001086537,0.0002361734],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971017,0.0002342874,0.002058815,0.0001727712,0.000009721844,0.0001352878,0.000003202635,0.0000099155,0.0002743039],"genre_scores_gemma":[0.995865,0.00009948543,0.003841519,0.00002271562,0.000005561376,0.00001894744,0.00001633386,0.000003238184,0.0001271874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1235352,"threshold_uncertainty_score":0.6316252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01816764844038726,"score_gpt":0.2655019527490269,"score_spread":0.2473343043086396,"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."}}