{"id":"W2809083129","doi":"10.3390/mi9060306","title":"Rapid Detection and Trapping of Extracellular Vesicles by Electrokinetic Concentration for Liquid Biopsy on Chip","year":2018,"lang":"en","type":"article","venue":"Micromachines","topic":"Extracellular vesicles in disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; Abu Dhabi Education Council; New York University Abu Dhabi","keywords":"Liquid biopsy; Microvesicles; Nanoparticle tracking analysis; Extracellular vesicle; Vesicle; Extracellular; Detection limit; Chemistry; Extracellular vesicles; Electrokinetic phenomena; Extracellular fluid; Microfluidics; Chromatography; Biophysics; Nanotechnology; Membrane; Materials science; Cancer; Biology; Biochemistry; Cell biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005349368,0.0006336895,0.0003910144,0.0004590076,0.0002511396,0.0005477802,0.0007209466,0.0008566097,0.001482706],"category_scores_gemma":[0.0006574378,0.0003677883,0.0002545102,0.000201202,0.0004108668,0.0005884769,0.0006250637,0.0006340938,0.0008860678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006318899,"about_ca_system_score_gemma":0.0005253682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005317714,"about_ca_topic_score_gemma":0.001237902,"domain_scores_codex":[0.9994185,0.0001001947,0.00003548708,0.0001412079,0.0002624065,0.000042174],"domain_scores_gemma":[0.9996767,0.0001542898,0.00005770717,0.00002715101,0.00006354488,0.00002066716],"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":[0.0000126042,0.00001402026,0.00005533114,0.0000422985,0.000004144547,0.00002118154,0.00001318421,0.0001085765,0.9951234,0.000243837,0.0001391306,0.004222368],"study_design_scores_gemma":[0.00001208732,0.0001050468,0.000471716,0.00001353299,0.000008672905,0.0001516996,0.0000182122,0.00583237,0.9890032,0.0001242677,0.004242917,0.00001614577],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2573273,0.006269261,0.7276633,0.001051623,0.0003575165,0.0007111642,0.0004883336,0.002023785,0.004107664],"genre_scores_gemma":[0.4679,0.002985613,0.5208686,0.0008344394,0.000108581,0.001070717,0.0004076706,0.0001529654,0.005671293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001482706,"threshold_uncertainty_score":0.00496012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006820241428848341,"score_gpt":0.2341503182612669,"score_spread":0.2273300768324186,"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."}}