{"id":"W4385358151","doi":"10.1093/fqsafe/fyad032","title":"Arsenic speciation in freshwater fish: challenges and research needs","year":2023,"lang":"en","type":"review","venue":"Food Quality and Safety","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health; University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Alberta Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Arsenic; Arsenobetaine; Genetic algorithm; Environmental chemistry; Inductively coupled plasma mass spectrometry; Chemistry; Mass spectrometry; Chromatography; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003081769,0.000155616,0.0004738293,0.0001757677,0.0001203056,0.00002650802,0.000104825,0.0002349247,0.0002140466],"category_scores_gemma":[0.0001703414,0.0001354266,0.00006180129,0.0003294621,0.0001524288,0.0001307876,0.0002660967,0.0003623474,0.000150921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001789896,"about_ca_system_score_gemma":0.00002228683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009809445,"about_ca_topic_score_gemma":0.01103683,"domain_scores_codex":[0.9977754,0.0007947251,0.0004958352,0.0003504663,0.0003482115,0.0002354057],"domain_scores_gemma":[0.9991296,0.0004775912,0.0001128467,0.0001948364,0.000009646467,0.00007548954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004954993,0.00001777466,0.00002273588,0.001306421,0.0000123542,0.000001377567,0.002200472,1.995317e-7,3.702348e-7,0.003885589,0.0001796005,0.9923682],"study_design_scores_gemma":[0.0001826138,0.00005612324,0.01001478,0.0008716537,0.00001722884,0.000003100533,0.0006582952,0.00001012501,5.170953e-7,0.001824864,0.9861903,0.0001703614],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001432744,0.9866233,0.000006399433,0.00157578,0.0001083724,0.0007988717,0.0001095008,0.00004385319,0.009301208],"genre_scores_gemma":[0.00087223,0.9974964,0.00002367031,0.00003870792,0.00005914868,0.00004286749,0.00009495317,0.00001530536,0.001356672],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9921978,"threshold_uncertainty_score":0.6158813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3160371657968034,"score_gpt":0.4158868983924965,"score_spread":0.09984973259569313,"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."}}