{"id":"W4377087920","doi":"10.1021/acssensors.2c01349","title":"Aptamer-Based Electrochemical Microfluidic Biosensor for the Detection of <i>Cryptosporidium parvum</i>","year":2023,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Sunnybrook Health Science Centre; McGill University Health Centre; Health Sciences Centre; University of Calgary; McGill University","funders":"Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Faculty of Engineering, McGill University; McGill University","keywords":"Aptamer; Cryptosporidium parvum; Biosensor; Cryptosporidium; Tap water; Detection limit; Microfluidics; Colloidal gold; Nanotechnology; Chromatography; Chemistry; Microbiology; Biology; Materials science; Molecular biology; Nanoparticle; Environmental science; 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":[0.0002443614,0.0004639129,0.0002603862,0.0002926744,0.0001745457,0.0002182947,0.0004532631,0.0006228909,0.0004192958],"category_scores_gemma":[0.0002841195,0.00022013,0.0002700471,0.0001717203,0.0002060856,0.0003349971,0.0002685292,0.0003406241,0.000228997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003996756,"about_ca_system_score_gemma":0.0003668404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00061767,"about_ca_topic_score_gemma":0.00131867,"domain_scores_codex":[0.9997606,0.00002732859,0.00001781595,0.00008502441,0.00007427548,0.00003502841],"domain_scores_gemma":[0.9999105,0.00002275531,0.00002701848,0.000005205413,0.00002186874,0.00001269029],"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":[0.00002039116,0.00001540781,0.0002313358,0.00007871616,0.00000505374,0.00003689138,0.00001041922,0.0001730437,0.9951682,0.0001023361,0.0000995806,0.00405864],"study_design_scores_gemma":[0.000009451043,0.000197471,0.001387129,0.000007382498,0.00001576311,0.000250216,0.00001390348,0.004779711,0.9910738,0.00005062975,0.002200563,0.00001407793],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8363568,0.01086363,0.1442764,0.001013461,0.0005682082,0.0002803503,0.0006662006,0.001327825,0.004647177],"genre_scores_gemma":[0.9165879,0.002658739,0.07757795,0.0003928996,0.00007561059,0.000120163,0.0002314172,0.00001771947,0.002337631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006228909,"threshold_uncertainty_score":0.002899885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01059722296225107,"score_gpt":0.2594662747440972,"score_spread":0.2488690517818462,"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."}}