{"id":"W2039544037","doi":"10.1021/ac9027033","title":"Multiple Spiking Species-Specific Isotope Dilution Analysis by Molecular Mass Spectrometry: Simultaneous Determination of Inorganic Mercury and Methylmercury in Fish Tissues","year":2010,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Research Council Canada; Ministerio de Ciencia e Innovación; Agence Nationale de la Recherche; Fundación Caja Castellón","keywords":"Chemistry; Methylmercury; Isotope dilution; Mercury (programming language); Mass spectrometry; Isotopomers; Certified reference materials; Derivatization; Chromatography; Isotope; Inductively coupled plasma mass spectrometry; Reagent; Analytical Chemistry (journal); Environmental chemistry; Detection limit; Bioaccumulation; Molecule","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002466273,0.000182933,0.0003528837,0.00008044171,0.00005890218,0.00003198156,0.0001571182,0.0001353166,0.001799843],"category_scores_gemma":[0.0004540329,0.0001810356,0.00009491193,0.0009933367,0.0003030715,0.0001312916,0.0001025609,0.0002688875,0.00001084391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000917974,"about_ca_system_score_gemma":0.000006298849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033537,"about_ca_topic_score_gemma":0.00009102838,"domain_scores_codex":[0.9986079,0.00003057626,0.0003645761,0.0003787785,0.0003513959,0.0002668162],"domain_scores_gemma":[0.9992269,0.0002414508,0.000123358,0.0002574678,0.00002305439,0.0001277724],"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":[0.000008339678,0.00005143408,0.1115152,0.00001538575,0.00004464616,0.00001299025,0.00009958678,0.00003154446,0.8869675,0.00001212083,0.000113749,0.001127565],"study_design_scores_gemma":[0.000402764,0.00003268002,0.06871904,0.00001204959,0.0002649009,0.000007134495,0.0003131305,0.0154154,0.9119489,0.0002228842,0.002289124,0.000371944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926327,0.00009836649,0.003458448,0.0001715077,0.00002180118,0.00008810077,0.00002501779,0.00001844721,0.00348561],"genre_scores_gemma":[0.9980261,0.0001233322,0.001407179,0.00004293868,0.00002466954,0.000004194737,0.00003917083,0.00001150398,0.0003209457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04279613,"threshold_uncertainty_score":0.9991127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007942296454290614,"score_gpt":0.2433696403305328,"score_spread":0.2354273438762422,"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."}}