{"id":"W4281778709","doi":"10.47611/jsrhs.v10i4.2207","title":"A Novel Approach to Bio-Friendly Microplastic Extraction with Ascidians","year":2022,"lang":"en","type":"article","venue":"Journal of Student Research","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Burnaby Hospital","funders":"Directorate for Biological Sciences","keywords":"Microplastics; Plastic pollution; Environmental science; Filtration (mathematics); Extraction (chemistry); Pollution; Environmental chemistry; Biofilter; Biofouling; Filter (signal processing); Pulp and paper industry; Environmental engineering; Biology; Ecology; Chemistry; Chromatography; Membrane; Engineering","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":[0.0001752544,0.0004819415,0.0002101396,0.0003639278,0.0002385822,0.0003415644,0.0003057856,0.0005151341,0.0006458148],"category_scores_gemma":[0.000153979,0.0001778791,0.0003152893,0.0003331765,0.0002532667,0.0003378708,0.000346069,0.0004242995,0.0004353273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001909333,"about_ca_system_score_gemma":0.0002594243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005755331,"about_ca_topic_score_gemma":0.001066903,"domain_scores_codex":[0.9998266,0.00001937587,0.00001656429,0.00004792921,0.00007276695,0.00001675086],"domain_scores_gemma":[0.9999126,0.00001174986,0.00002582022,0.00001264564,0.0000239213,0.00001320619],"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":[0.00001371626,0.00001669932,0.00009414364,0.0000706841,0.000003293136,0.00007550723,0.00001902703,0.00005483072,0.9949481,0.0001130104,0.00005866829,0.004532121],"study_design_scores_gemma":[0.000008823277,0.0003431979,0.001862957,0.00001481209,0.00001669757,0.0004134313,0.00003002509,0.001066091,0.9880506,0.00009278246,0.008088703,0.00001188864],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8610761,0.005765052,0.1235,0.0005470637,0.0002211598,0.000551124,0.0006476159,0.0006843384,0.007007338],"genre_scores_gemma":[0.8692046,0.004462188,0.1171444,0.0003471443,0.00003836234,0.0002192722,0.0004877074,0.00004114352,0.008055235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006458148,"threshold_uncertainty_score":0.00216049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0604235275114887,"score_gpt":0.3429224176378952,"score_spread":0.2824988901264064,"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."}}