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Record W2594326548

Impedance Spectroscopy of Single Cells Using Embedded AgPDMS Electrodes

2015· dissertation· en· W2594326548 on OpenAlexfundno aff
Yuan Wei

Bibliographic record

VenueTSpace (University of Toronto) · 2015
Typedissertation
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsDielectric spectroscopyElectrodeElectrical impedanceSpectroscopyMaterials scienceOptoelectronicsElectrical engineeringEngineeringChemistryPhysicsElectrochemistry
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a microfluidic device with wide channels and embedded AgPDMS electrodes for measuring the electrical properties of single cells. The work demonstrates the feasibility of using a large channel design and embedded electrodes for impedance spectroscopy to circumvent issues such as channel clogging and limited device re-usability. AgPDMS electrodes were formed on channel sidewalls for impedance detection and cell characterization. Equivalent circuit models were used to interpret multi-frequency impedance data to quantify the cytoplasm conductivity and specific membrane capacitance of each cell. T24 cells were tested to validate the microfluidic system and modeling results. Comparisons were then made by measuring two leukemia cell lines (AML-2 and HL-60) which were found to have different cytoplasm conductivity values (0.29 ± 0.15 S/m vs. 0.47 ± 0.20 S/m) and specific membrane capacitance values (41 ± 25 mF/m2 vs. 55 ± 26 mF/m2).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.257
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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