{"id":"W2076161522","doi":"10.1063/1.4746249","title":"Quantification of the specific membrane capacitance of single cells using a microfluidic device and impedance spectroscopy measurement","year":2012,"lang":"en","type":"article","venue":"Biomicrofluidics","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Microfluidics; Capacitance; Dielectric spectroscopy; Materials science; Electrical impedance; Membrane; Equivalent circuit; Optoelectronics; Analytical Chemistry (journal); Biomedical engineering; Voltage; Biophysics; Nanotechnology; Chemistry; Electrode; Electrical engineering; Chromatography; Biology; Electrochemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005117352,0.0002534815,0.0003437267,0.0001211237,0.00008840505,0.0000185932,0.0002949778,0.0001802161,0.000005039456],"category_scores_gemma":[0.00002868661,0.0002083021,0.00009389545,0.0004482364,0.0004259712,0.0001210647,0.00006417067,0.0001368612,0.000004589003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001946316,"about_ca_system_score_gemma":0.00003612464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003380721,"about_ca_topic_score_gemma":0.000001204601,"domain_scores_codex":[0.9985183,0.0000489104,0.0005322756,0.0002157375,0.0002837138,0.0004010139],"domain_scores_gemma":[0.9989962,0.00003647367,0.0001894477,0.0005815591,0.0001407683,0.00005557566],"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":[0.00001340574,0.00006772838,0.0007798808,0.0002338307,0.00003385027,2.19302e-7,0.0002210178,0.000001803292,0.9939601,0.0001537033,0.003699715,0.0008346787],"study_design_scores_gemma":[0.0002206511,0.00002299112,0.0004673534,0.0001829006,0.00004921783,0.00001685736,0.0002017969,0.00009339656,0.991241,0.00002655259,0.007263098,0.0002141524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8588937,0.1271242,0.0127666,0.00003945165,0.0007102794,0.0002594968,0.00003852689,0.0001118767,0.00005588361],"genre_scores_gemma":[0.9822246,0.01385025,0.003796835,0.00001365672,0.0000653401,0.000002074634,0.000001970993,0.0000399121,0.000005345895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1233309,"threshold_uncertainty_score":0.8494313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05365538312637102,"score_gpt":0.2237419751199707,"score_spread":0.1700865919935996,"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."}}