{"id":"W3083093693","doi":"10.1016/j.talanta.2020.121618","title":"Highly sensitive magnetic-microparticle-based aptasensor for Cryptosporidium parvum oocyst detection in river water and wastewater: Effect of truncation on aptamer affinity","year":2020,"lang":"en","type":"article","venue":"Talanta","topic":"Parasitic Infections and Diagnostics","field":"Immunology and Microbiology","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Health Canada; Carleton University; National Research Council Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Aptamer; Cryptosporidium parvum; Chemistry; Detection limit; Chromatography; Wastewater; Cryptosporidium; Flow cytometry; Molecular biology; Microbiology; Biology; Environmental engineering","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":[0.000403646,0.0003889459,0.0003826387,0.0001783827,0.000188237,0.000252789,0.0003165799,0.0006762298,0.0004910249],"category_scores_gemma":[0.0004239191,0.0002434489,0.0002186169,0.000129542,0.0002059002,0.00024246,0.0002284568,0.0004746411,0.0002878244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002667018,"about_ca_system_score_gemma":0.0001876433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003742893,"about_ca_topic_score_gemma":0.00102342,"domain_scores_codex":[0.9996762,0.00005239404,0.00002680677,0.00009219289,0.0001070338,0.0000454281],"domain_scores_gemma":[0.9997972,0.00005807206,0.00003586676,0.00001310928,0.00006019254,0.00003558907],"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":[0.00002005916,0.000007793332,0.00002672993,0.0000126931,0.000001833882,0.000007276268,0.000006235771,0.00001691065,0.9994444,0.000007049604,0.000009555913,0.0004394603],"study_design_scores_gemma":[0.000004638771,0.0001051064,0.0005104736,0.000001376456,0.000006690853,0.00006553439,0.000006908381,0.0007172316,0.9982355,0.000008909053,0.0003332789,0.000004459353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.980383,0.00112753,0.01718272,0.0001519204,0.00006967161,0.00005247731,0.0001540166,0.0001583992,0.0007202599],"genre_scores_gemma":[0.9794684,0.0005587757,0.01712459,0.0001609346,0.00002636696,0.00006192752,0.0002145634,0.00002177745,0.002362694],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0006762298,"threshold_uncertainty_score":0.002134681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008584881508281721,"score_gpt":0.218923341124718,"score_spread":0.2103384596164363,"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."}}