{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001503447,0.0003669082,0.0004211245,0.0001745813,0.0004107642,0.0003250312,0.0005918996,0.0007446262,0.0007663337],"category_scores_gemma":[0.0001789437,0.0003884375,0.0003859315,0.0000952451,0.0004020617,0.0003049376,0.0004208227,0.0004272879,0.0004546367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003943825,"about_ca_system_score_gemma":0.000209144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003473807,"about_ca_topic_score_gemma":0.01048099,"domain_scores_codex":[0.9998105,0.00001197095,0.00001181185,0.00009311102,0.00004729291,0.0000253485],"domain_scores_gemma":[0.9998509,0.00001423404,0.000028249,0.00001907794,0.00005245314,0.00003507845],"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":[0.0001308136,0.00001689942,0.001450552,0.00005202476,0.00001576269,0.00005692563,0.00006167255,0.00006542809,0.9930328,0.00003543777,0.00003896951,0.005042692],"study_design_scores_gemma":[0.00002230779,0.0008120549,0.02528844,0.00001099356,0.0001266768,0.0007470325,0.0001696269,0.001655608,0.9671838,0.00007519959,0.003868568,0.00003960794],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750905,0.0003966634,0.02277993,0.00009365572,0.00003532371,0.0001202155,0.000152753,0.000247401,0.001083435],"genre_scores_gemma":[0.8914753,0.0002527221,0.09992336,0.0002433659,0.000009842124,0.0001535875,0.0004268429,0.0001191995,0.007395679],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003473807,"threshold_uncertainty_score":0.006907225,"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."}}