{"id":"W2288445349","doi":"10.4236/jep.2016.73037","title":"Trace-Level Analysis of Hexavalent Chromium in Lake Sediment Samples Using Ion Chromatography Tandem Mass Spectrometry","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Protection","topic":"Chromium effects and bioremediation","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ministry of Energy, Northern Development and Mines; Ministry of the Environment, Conservation and Parks","funders":"Duquesne University","keywords":"Isotope dilution; Hexavalent chromium; Chemistry; Sediment; Environmental chemistry; Certified reference materials; Chromium; Mass spectrometry; Extraction (chemistry); Chromatography; Detection limit; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000718038,0.0001670321,0.0003530681,0.0005253164,0.00005662161,0.0000124421,0.0001281076,0.0001023999,0.001584128],"category_scores_gemma":[0.00002160163,0.0001158047,0.0002803998,0.0006931665,0.0001460972,0.0003814889,0.00004933899,0.0001400898,0.000008608626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008798685,"about_ca_system_score_gemma":0.000009072461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007390814,"about_ca_topic_score_gemma":0.0001906895,"domain_scores_codex":[0.9981552,0.000125926,0.0006383076,0.0002249375,0.0006434982,0.0002121502],"domain_scores_gemma":[0.9990088,0.0000432168,0.0007133789,0.0001447988,0.000004069754,0.00008574647],"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":[0.00006918005,0.000231034,0.1533856,0.000006934034,0.0001426315,0.000004767531,0.00006175339,0.002328609,0.8399367,7.901882e-7,0.000006135458,0.003825883],"study_design_scores_gemma":[0.0009277875,0.0004142378,0.8198086,0.00005352843,0.0002468008,0.0000188057,0.00007401894,0.001193975,0.1769452,0.00006046299,0.0001215751,0.0001349662],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785069,0.00007147313,0.02080068,0.00008237374,0.000152807,0.0003000646,0.00004537813,0.000005230903,0.00003514136],"genre_scores_gemma":[0.9977603,0.0001433854,0.001956757,0.00001031358,0.00009546606,0.000004633277,0.000002898907,0.00001233949,0.00001393982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.666423,"threshold_uncertainty_score":0.9993286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0208238301548926,"score_gpt":0.2228792879256452,"score_spread":0.2020554577707526,"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."}}