{"id":"W4398154849","doi":"10.12911/22998993/188121","title":"Evaluating Microplastics Removal Efficiency of Textile Industry Conventional Wastewater Treatment Plant of Thailand","year":2024,"lang":"en","type":"article","venue":"Journal of Ecological Engineering","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Asian Institute of Technology","keywords":"Microplastics; Textile; Wastewater; Textile industry; Environmental science; Sewage treatment; Waste management; Pulp and paper industry; Environmental engineering; Engineering; Biology; Ecology; Geography","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":[0.0002677568,0.0002991006,0.0003200996,0.0006592931,0.0004854538,0.0007647105,0.0002293182,0.0003618725,0.0009808597],"category_scores_gemma":[0.0003739409,0.0001344814,0.0003774911,0.0008158254,0.0002039099,0.0004046174,0.0003523833,0.000286616,0.0002852227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004242779,"about_ca_system_score_gemma":0.0004685024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01130041,"about_ca_topic_score_gemma":0.012319,"domain_scores_codex":[0.9996184,0.00004612678,0.00005022237,0.00006034954,0.0001694727,0.00005544729],"domain_scores_gemma":[0.9996079,0.0000739086,0.00009237791,0.00001301815,0.0001685705,0.00004432408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001449434,0.0007268387,0.1132512,0.001459759,0.0001145758,0.001025111,0.001273368,0.005823617,0.8432946,0.00009576303,0.0002609482,0.03122482],"study_design_scores_gemma":[0.0000457358,0.00609135,0.3264721,0.00007696341,0.000234339,0.0007339612,0.004570223,0.009988351,0.6490855,0.00008315944,0.002544394,0.00007394225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991691,0.00009643707,0.0001681981,0.000009206245,0.000001342741,0.00001104719,0.0001028378,0.000004507885,0.0004373035],"genre_scores_gemma":[0.9979352,0.0003391415,0.0004476759,0.00001476867,0.000001675179,0.00001616692,0.0002160143,0.000005319409,0.001024031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01130041,"threshold_uncertainty_score":0.02246928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02349350072594336,"score_gpt":0.2513657721742685,"score_spread":0.2278722714483252,"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."}}