{"id":"W3185225190","doi":"10.1002/etc.5179","title":"Microwave-Assisted Extraction for Quantification of Microplastics Using Pyrolysis–Gas Chromatography/Mass Spectrometry","year":2021,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; Herbert W. Hoover Foundation; Georgia Aquarium","keywords":"Microplastics; Detection limit; Chromatography; Extraction (chemistry); Polypropylene; Gas chromatography–mass spectrometry; Gas chromatography; Polycarbonate; Mass spectrometry; Polystyrene; Chemistry; Environmental chemistry; Polymer; Organic chemistry","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009552253,0.0001530467,0.0001891888,0.00002154675,0.0001601617,0.00001273257,0.00007089152,0.0002018427,0.001328787],"category_scores_gemma":[0.0000355268,0.0001720093,0.00008126244,0.0001132771,0.0003325354,0.00005795061,0.00006231904,0.0001172228,0.00001160255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001312324,"about_ca_system_score_gemma":0.00001549446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004552273,"about_ca_topic_score_gemma":0.00000600093,"domain_scores_codex":[0.9990061,0.00002595833,0.0002765145,0.0003593755,0.0001108094,0.000221275],"domain_scores_gemma":[0.9994442,0.0001203447,0.00018678,0.000166508,0.000003574449,0.00007853412],"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":[0.00004344545,0.0002156254,0.009614281,0.00004077352,0.00003951695,0.00000603469,0.00002638919,0.0002201394,0.9889531,0.00001144858,0.0000907955,0.0007384628],"study_design_scores_gemma":[0.0004458835,0.00004026769,0.02598769,0.00001147676,0.00009933289,0.0001714636,0.000139455,0.001980183,0.9700976,0.0001538829,0.0007075804,0.0001651924],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495797,0.0002442021,0.04954889,0.00002037397,0.0001144052,0.00008748284,0.0001161194,0.000009480126,0.0002794038],"genre_scores_gemma":[0.9830415,0.0001251542,0.01645999,0.00002360604,0.00003854867,0.000007053915,0.0001149166,0.00001389388,0.0001753793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03346182,"threshold_uncertainty_score":0.9995841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129229805238413,"score_gpt":0.2258191988896383,"score_spread":0.2145269008372541,"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."}}