{"id":"W4410121212","doi":"10.3390/bios15050294","title":"An Extracellular Vesicle (EV) Paper Strip for Rapid and Convenient Estimation of EV Concentration","year":2025,"lang":"en","type":"article","venue":"Biosensors","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; University of Guelph","keywords":"Nitrocellulose; Extracellular vesicles; Dilution; Fluorescence; Chromatography; Immunoassay; Chemistry; Repeatability; Membrane; Materials science; Computer science; Nanotechnology; Biomedical engineering; Analytical Chemistry (journal); Antibody; Biochemistry; Biology","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":[0.001087798,0.001236321,0.0004810879,0.0008444291,0.000235654,0.000730242,0.000939212,0.001351563,0.001002281],"category_scores_gemma":[0.001043604,0.0004055753,0.00047433,0.0004077682,0.0003053862,0.0005427025,0.0006039669,0.0008475924,0.001076954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002920659,"about_ca_system_score_gemma":0.000291524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001541176,"about_ca_topic_score_gemma":0.0002735513,"domain_scores_codex":[0.9988324,0.0002536107,0.00006913591,0.0003034281,0.0004838079,0.00005761671],"domain_scores_gemma":[0.9994337,0.0002195597,0.0001219593,0.00004258678,0.0001451305,0.00003698296],"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":[0.00005355641,0.00003288372,0.0003664102,0.0001342733,0.00001616471,0.00006311582,0.00002311363,0.0000815136,0.9880244,0.0001998618,0.0002894762,0.01071519],"study_design_scores_gemma":[0.000007108947,0.000238656,0.00133409,0.0000260601,0.00002769149,0.0006060452,0.00002977764,0.002858363,0.9890494,0.0001183963,0.005685292,0.00001917733],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2393637,0.01198106,0.7355868,0.0008021596,0.0009350945,0.0007030288,0.001215943,0.003076622,0.006335652],"genre_scores_gemma":[0.4096997,0.007524927,0.5688679,0.0008678754,0.0002334995,0.0007567455,0.001475579,0.0001402951,0.01043349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001351563,"threshold_uncertainty_score":0.005752921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006750093499957538,"score_gpt":0.265350745157749,"score_spread":0.2586006516577915,"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."}}