{"id":"W1986465756","doi":"10.1039/b007518n","title":"Application of column switching in high-performance liquid chromatography with on-line thermo-oxidation and detection by HG-AAS and HG-AFS for the analysis of organoarsenical species in seafood samples","year":2001,"lang":"en","type":"article","venue":"Journal of Analytical Atomic Spectrometry","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Arsenobetaine; Chemistry; Certified reference materials; Chromatography; Arsenate; Detection limit; Atomic absorption spectroscopy; Arsenite; Arsenic; Elution; Analytical Chemistry (journal)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005387211,0.00008841047,0.0002911461,0.0004038766,0.00004090372,0.00001171833,0.00008761483,0.00005079276,0.0000545429],"category_scores_gemma":[0.00007050707,0.00006231372,0.00005576015,0.001420217,0.0001696183,0.0001559488,0.00002218674,0.0001356099,3.026729e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185149,"about_ca_system_score_gemma":0.00001105632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001348201,"about_ca_topic_score_gemma":0.0007020651,"domain_scores_codex":[0.9989644,0.0000365854,0.0004793966,0.0001465702,0.000261429,0.0001116242],"domain_scores_gemma":[0.9992007,0.0002725675,0.0003536995,0.0001005919,0.0000294914,0.000042957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001397736,0.0003879184,0.6223686,0.00003184409,0.0004134538,0.0000019334,0.0004849861,0.002742733,0.342627,0.0007797634,0.00001131541,0.02875273],"study_design_scores_gemma":[0.000868515,0.0006782181,0.8746858,0.00002152099,0.0002271714,0.00001402543,0.000389708,0.09602179,0.02686941,0.000121461,0.00003001186,0.00007236639],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589406,0.00004035912,0.04047609,0.000327998,0.000009072661,0.0001611124,0.000003546415,0.000002588158,0.00003863365],"genre_scores_gemma":[0.9992492,0.0002317645,0.0004530513,0.00002987215,0.00001619354,0.000002704262,0.000003481314,0.000005785058,0.000007947564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3157576,"threshold_uncertainty_score":0.254108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008057258713463569,"score_gpt":0.2280757760227776,"score_spread":0.220018517309314,"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."}}