{"id":"W2162422205","doi":"10.1002/etc.2184","title":"Determination of mercury speciation in fish tissue with a direct mercury analyzer","year":2013,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Institut National de la Recherche Scientifique","funders":"","keywords":"Methylmercury; Mercury (programming language); Environmental chemistry; Certified reference materials; Chemistry; Atomic absorption spectroscopy; Genetic algorithm; Thallium; Bioaccumulation; Chromatography; Detection limit; Inorganic chemistry; Ecology; Biology","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":[0.0005998785,0.0006870123,0.0004723935,0.0009732108,0.0004585764,0.0004577135,0.0008852142,0.0006677974,0.002580095],"category_scores_gemma":[0.000808903,0.0004886658,0.0004780691,0.0005880054,0.000558411,0.0005241325,0.00102197,0.0008069305,0.001443711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008492999,"about_ca_system_score_gemma":0.001022056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003015256,"about_ca_topic_score_gemma":0.009184035,"domain_scores_codex":[0.9986826,0.00008173675,0.00005911729,0.0004518998,0.0006812998,0.00004327329],"domain_scores_gemma":[0.9994673,0.00009007965,0.00009241761,0.00008908973,0.0002237186,0.00003732054],"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":[0.00003255852,0.00001309234,0.001881024,0.00006182511,0.00001711611,0.00002646002,0.00003068424,0.00007028502,0.9906932,0.00008349523,0.00008333453,0.007006953],"study_design_scores_gemma":[0.00003397851,0.0004192769,0.01295712,0.00001264216,0.00009817955,0.000613844,0.00004890252,0.004716757,0.9749509,0.0001696549,0.00594224,0.00003652684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4959596,0.001847153,0.4851291,0.0003253294,0.0002328957,0.0008223685,0.002091348,0.00285611,0.01073604],"genre_scores_gemma":[0.464963,0.002352602,0.5080428,0.000526075,0.00007951397,0.001040797,0.001273601,0.0002074457,0.02151418],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003015256,"threshold_uncertainty_score":0.008631289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005453113282881778,"score_gpt":0.2156177775558688,"score_spread":0.210164664272987,"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."}}