{"id":"W2551747717","doi":"10.1016/j.jes.2016.10.009","title":"Characterization of colloidal arsenic at two abandoned gold mine sites in Nova Scotia, Canada, using asymmetric flow-field flow fractionation-inductively coupled plasma mass spectrometry","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Sciences","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University","funders":"Natural Resources Canada; Natural Sciences and Engineering Research Council of Canada; Queen's University; Trent University; University of Ottawa","keywords":"Arsenic; Colloid; Inductively coupled plasma mass spectrometry; Fractionation; Chemistry; Inductively coupled plasma; Mass spectrometry; Field flow fractionation; Environmental chemistry; Chromatography; Nova scotia; Mineralogy; Analytical Chemistry (journal); Geology; Plasma","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":[0.0002155185,0.0003996009,0.0004683752,0.001685942,0.003393992,0.001339006,0.0009332364,0.0006698467,0.0004577216],"category_scores_gemma":[0.0003941873,0.0002953212,0.0002585294,0.001034622,0.0008527958,0.0002241608,0.0005893537,0.0003396776,0.000165612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007623609,"about_ca_system_score_gemma":0.009676689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9629962,"about_ca_topic_score_gemma":0.9863998,"domain_scores_codex":[0.999613,0.00001735841,0.0000208734,0.00006494574,0.0001940193,0.00008993963],"domain_scores_gemma":[0.9995229,0.00003175021,0.00004752808,0.000008817263,0.0003237694,0.00006518101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006142202,0.0001952765,0.771809,0.0002483284,0.0001573863,0.002907272,0.006710172,0.002349311,0.1945034,0.0004066949,0.0009567495,0.01914219],"study_design_scores_gemma":[0.00002716317,0.000093304,0.9810683,0.00002886644,0.000041756,0.0003275018,0.00510578,0.002649002,0.008358817,0.00005578763,0.002216281,0.00002743724],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977089,0.00007497405,0.0003287198,0.00003994066,0.000004954525,0.00005077538,0.0003411153,0.000009243639,0.001441316],"genre_scores_gemma":[0.9952908,0.0001031109,0.001113568,0.00005132638,0.000002665495,0.00002200397,0.0002924474,0.000007637269,0.003116661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03700382,"threshold_uncertainty_score":0.0744434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109852964485192,"score_gpt":0.221453879693594,"score_spread":0.2103553500487421,"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."}}