{"id":"W2285360399","doi":"10.1021/acs.analchem.5b00712","title":"Three Birds with One Fe<sub>3</sub>O<sub>4</sub> Nanoparticle: Integration of Microwave Digestion, Solid Phase Extraction, and Magnetic Separation for Sensitive Determination of Arsenic and Antimony in Fish","year":2015,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Electrochemical Analysis and Applications","field":"Chemistry","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China","keywords":"Chemistry; Antimony; Arsenic; Certified reference materials; Detection limit; Microwave digestion; Extraction (chemistry); Sample preparation; Nanoparticle; Magnetic nanoparticles; Analytical Chemistry (journal); Inductively coupled plasma mass spectrometry; Solid phase extraction; Chromatography; Mass spectrometry; Nuclear chemistry; Inorganic chemistry; Nanotechnology; Materials science","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":[0.0001738317,0.0001907058,0.0003559706,0.00005026972,0.00004817491,0.00003128746,0.00005928141,0.0001801685,0.000003086613],"category_scores_gemma":[0.0002021778,0.0001847701,0.00006227868,0.0003127845,0.0002223683,0.0001418529,0.00002563784,0.000173179,6.996976e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007376329,"about_ca_system_score_gemma":0.0000792774,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001071884,"about_ca_topic_score_gemma":0.0001562375,"domain_scores_codex":[0.9986581,0.00001152734,0.0005171813,0.0003846388,0.0002190556,0.000209529],"domain_scores_gemma":[0.9988106,0.0001615862,0.0002599623,0.0002051578,0.0004193834,0.0001433322],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002011473,0.000385921,0.0006582547,0.0001541587,0.0000371186,0.000001726176,0.0000752692,0.000008641405,0.9863748,0.00004420256,0.00003513463,0.01202366],"study_design_scores_gemma":[0.00127846,0.0001073686,0.0005525798,0.000115482,0.0002694782,0.00001932646,0.0001259309,0.0582865,0.9380493,0.001007919,0.000005479542,0.0001822166],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816885,0.0000544716,0.01770994,0.0002453796,0.000003111312,0.0001362172,0.00003753514,0.00001941898,0.0001054075],"genre_scores_gemma":[0.9989085,0.00006608452,0.0006844322,0.00001906618,0.00005073579,0.00004394314,0.0001981584,0.00001795394,0.00001116587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05827785,"threshold_uncertainty_score":0.7534704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160484533971496,"score_gpt":0.2888469328637408,"score_spread":0.2727984794665912,"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."}}