{"id":"W3041008619","doi":"10.1016/j.envpol.2020.115190","title":"Arsenic speciation in sea cucumbers: Identification and quantitation of water-extractable species","year":2020,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Echinoderm biology and ecology","field":"Agricultural and Biological Sciences","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland; National Research Council Canada","funders":"","keywords":"Sea cucumber; Apostichopus japonicus; Biology; Seawater; Arsenobetaine; Inductively coupled plasma mass spectrometry; Environmental chemistry; Chemistry; Ecology; Chromatography; Mass spectrometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011001,0.00005409683,0.00007952026,0.000009180091,0.00005519324,0.000006873407,0.00004081473,0.00007175488,0.0003558548],"category_scores_gemma":[0.00001261116,0.00002589669,0.00002005667,0.0000511696,0.00006400845,0.0001669617,0.00002480714,0.00005337225,0.0000529199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002691669,"about_ca_system_score_gemma":8.178968e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009435308,"about_ca_topic_score_gemma":0.0005523232,"domain_scores_codex":[0.9994655,0.00005290664,0.0001734885,0.0001493028,0.00005521433,0.0001036432],"domain_scores_gemma":[0.9998708,0.00002086798,0.00006354932,0.00001764009,0.000001631478,0.00002551672],"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":[0.00002173618,0.00003517952,0.1840319,0.000002658757,0.000002273778,3.46394e-7,0.0002600269,0.00002572837,0.8132412,0.0001071154,0.00002445962,0.002247297],"study_design_scores_gemma":[0.0001014288,0.0001004134,0.9078602,0.000002125709,0.000004134646,0.000001321863,0.000559599,0.0005794044,0.08992708,0.000322029,0.0004882701,0.00005403936],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971949,0.00007760366,0.0000152933,0.002389412,0.00004304579,0.0001006355,0.00002745165,0.000009432748,0.0001422352],"genre_scores_gemma":[0.9993868,0.0001256195,0.00002058167,0.0001169126,0.00005451563,0.000002107377,0.0002254332,4.477864e-7,0.00006754863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7238282,"threshold_uncertainty_score":0.3896361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0164150428862015,"score_gpt":0.1830193356116387,"score_spread":0.1666042927254372,"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."}}