{"id":"W4404839603","doi":"10.1002/ange.202421438","title":"Selection of Plastic‐Binding DNA Aptamers for Microplastics Detection","year":2024,"lang":"en","type":"article","venue":"Angewandte Chemie","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Global Water Futures; Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund; Shanghai Jiao Tong University; China Scholarship Council; University of Waterloo","keywords":"Microplastics; Aptamer; DNA; Chemistry; Selection (genetic algorithm); Computational biology; Nanotechnology; Biology; Materials science; Genetics; Environmental chemistry; Computer science; Biochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000224013,0.0003888501,0.0002177517,0.0003672069,0.0001534144,0.0002530369,0.0002033234,0.000371743,0.0007291308],"category_scores_gemma":[0.0003701935,0.0001942008,0.0001962865,0.0002175946,0.0001905904,0.0001446462,0.0001691498,0.0003176447,0.0004364057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002641867,"about_ca_system_score_gemma":0.0001480941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003056874,"about_ca_topic_score_gemma":0.0005513203,"domain_scores_codex":[0.9997696,0.00005070693,0.00001332913,0.00006551216,0.00006233206,0.000038429],"domain_scores_gemma":[0.99979,0.00007591391,0.00004245927,0.00001585582,0.00004105908,0.00003471299],"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":[0.00001602696,0.000007626413,0.0001237993,0.00001268916,0.000001709089,0.00001421414,0.00000736007,0.0001463877,0.998674,0.00002570301,0.00001269271,0.0009578262],"study_design_scores_gemma":[0.00000257337,0.00004810434,0.000389045,0.000001370995,0.000002149396,0.00004025398,0.000006291248,0.001434716,0.9976298,0.00001667968,0.0004262451,0.000002824045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712664,0.0008341775,0.02603624,0.00009356802,0.00004608873,0.00008916606,0.0002023117,0.0001341127,0.001297916],"genre_scores_gemma":[0.9763901,0.0003129479,0.02141567,0.00006317558,0.000008738145,0.00006020254,0.0001920589,0.00002426929,0.001532833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007291308,"threshold_uncertainty_score":0.002439201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01049349495606879,"score_gpt":0.2176559575064696,"score_spread":0.2071624625504008,"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."}}