{"id":"W3126468716","doi":"10.1016/b978-0-12-819952-7.00013-5","title":"Molecularly imprinted polymer composites in wastewater treatment","year":2021,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Molecularly imprinted polymer; Materials science; Adsorption; Carbon nanotube; Molecular imprinting; Wastewater; Solid phase extraction; Molecular recognition; Composite number; Polymer; Sewage treatment; Graphene; Aqueous solution; Nanotechnology; Extraction (chemistry); Composite material; Selectivity; Molecule; Chemistry; Catalysis; Chromatography; Organic chemistry; Environmental science; Environmental 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":[0.0001406353,0.0007510218,0.0004411576,0.0006593328,0.0002224058,0.001009569,0.000604848,0.0007940938,0.01687688],"category_scores_gemma":[0.0000980503,0.0004782578,0.0002679024,0.0008294232,0.000211338,0.00113026,0.0005495554,0.0009595887,0.01333309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003357894,"about_ca_system_score_gemma":0.0002106405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004378427,"about_ca_topic_score_gemma":0.001117603,"domain_scores_codex":[0.9998617,0.000008685129,0.000004769999,0.00002531213,0.00008848808,0.00001103584],"domain_scores_gemma":[0.9999621,0.00001718943,0.000003954424,0.000003679926,0.000009801023,0.000003318097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007885847,0.0001988764,0.000089845,0.001413523,0.00001989019,0.0003258406,0.00009656277,0.002148687,0.2836561,0.01216026,0.03377005,0.6660415],"study_design_scores_gemma":[0.000009357128,0.0001511421,0.0005672839,0.0002434401,0.00002950309,0.0008709942,0.00004578112,0.003911753,0.2649925,0.004571455,0.7245786,0.00002828307],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02242686,0.2267272,0.1210301,0.001119295,0.003936943,0.0001577194,0.0005459727,0.002710576,0.6213453],"genre_scores_gemma":[0.02780557,0.06216801,0.02098398,0.0005229067,0.0003810441,0.00006008683,0.0002671735,0.0003524671,0.8874587],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01687688,"threshold_uncertainty_score":0.05645877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962983263101612,"score_gpt":0.2585307943153019,"score_spread":0.2389009616842858,"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."}}