{"id":"W1985307351","doi":"10.1021/es900086r","title":"Arsenic Speciation of Terrestrial Invertebrates","year":2009,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Simon Fraser University","funders":"National Research Council Canada","keywords":"Arsenobetaine; Arsenic; Environmental chemistry; Arsenate; Genetic algorithm; Metalloid; Arsenite; Invertebrate; Chemistry; Inductively coupled plasma mass spectrometry; Biology; Ecology; Mass spectrometry; Chromatography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0000568515,0.0002309278,0.0001347088,0.0008280345,0.0007277732,0.0003787838,0.0001223736,0.0001237502,0.0007338099],"category_scores_gemma":[0.00009421424,0.0001216067,0.0001098451,0.0005108207,0.0001712337,0.00008254257,0.000156162,0.00009779221,0.0001963934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007374823,"about_ca_system_score_gemma":0.0004479119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08512006,"about_ca_topic_score_gemma":0.1840023,"domain_scores_codex":[0.9999193,0.000006115423,0.000004434515,0.00002613111,0.00002645308,0.0000176132],"domain_scores_gemma":[0.9999346,0.000003877602,0.00001084249,0.000002240027,0.00003645946,0.00001201256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000222479,0.00001354151,0.1744335,0.0001127986,0.00004508545,0.0003288717,0.0003877374,0.0003526864,0.8122653,0.00007760725,0.0001117664,0.01164862],"study_design_scores_gemma":[0.000005689384,0.0002832007,0.9260162,0.00001584834,0.00003672823,0.0005504384,0.0005504264,0.0004489541,0.06924891,0.00006496561,0.002767599,0.00001119838],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973895,0.0002803395,0.0002598041,0.000007422985,0.00000118311,0.000007662262,0.0003850414,0.00001083679,0.001658166],"genre_scores_gemma":[0.9956651,0.0004223492,0.0006407597,0.00001929544,0.000001505083,0.000005715799,0.0005097352,0.000004857732,0.002730603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08512006,"threshold_uncertainty_score":0.1692492,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00473185952251897,"score_gpt":0.2055442112581698,"score_spread":0.2008123517356508,"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."}}