{"id":"W7132984752","doi":"","title":"Identification of Microplastics in Drinking Water Using Pyrolysis-GC/MS","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Microplastics; Polyvinyl chloride; Turbidity; Polypropylene; Polyethylene; Pyrolysis; Polycarbonate; Extraction (chemistry)","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":[0.0003026368,0.0006163054,0.0003039962,0.001752677,0.0007145038,0.0003561027,0.0003234547,0.0002749866,0.001634232],"category_scores_gemma":[0.0004094129,0.0002058327,0.0003106307,0.001075276,0.0004343354,0.0002160054,0.0003195675,0.000430693,0.0005634683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009904664,"about_ca_system_score_gemma":0.001728759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04108864,"about_ca_topic_score_gemma":0.08548917,"domain_scores_codex":[0.9995402,0.00001771519,0.0000182249,0.0001041352,0.0002647965,0.00005502204],"domain_scores_gemma":[0.9997583,0.00003796547,0.00002660158,0.000007436798,0.0001493816,0.00002038467],"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":[0.0000642083,0.00003139531,0.003825242,0.0001352221,0.00001889738,0.00007017874,0.0001153464,0.0001773291,0.9816946,0.00004911607,0.00008250243,0.01373602],"study_design_scores_gemma":[0.000007208875,0.000207763,0.06386413,0.00003787547,0.00004366434,0.0002797736,0.0002699461,0.001487013,0.9286147,0.0000887186,0.005070126,0.00002920132],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9431552,0.003402051,0.03746254,0.0001183103,0.00004395441,0.0006239319,0.005360049,0.0005333761,0.009300572],"genre_scores_gemma":[0.9097149,0.005180853,0.06846063,0.0002212856,0.0000184323,0.0004857478,0.002481246,0.00009853693,0.01333839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04108864,"threshold_uncertainty_score":0.08169895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311536557904566,"score_gpt":0.2729637555719296,"score_spread":0.2598483899928839,"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."}}