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Record W2004249619 · doi:10.1109/ccece.2014.6900984

A hybrid device for electrical impedance tomography and bioelectrical impedance spectroscopy measurement

2014· article· en· W2004249619 on OpenAlexaff
Markéta Michalíková, Michal Prauzek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCalibrationElectrical impedanceAcousticsNoise (video)Electrical impedance tomographyElectronic engineeringElectrical engineeringComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

We proposed a hybrid device, which is capable of measuring either bioelectrical impedance spectroscopy (BIS) or electrical impedance tomography (EIT) based on the Magnitude Ratio and Phase Difference Detection method. Frequency range available for measuring is from 1 kHz to 1 MHz. The device is based on The Freescale Tower system module with S08MM Freescale microcontroller. The proposed device is divided into two modules. One of them includes measurement chain, the second one contains four multiplexers, which connect always four electrodes to the circuit from total amount of sixteen electrodes. Both modules are connected via Tower elevator modules. While measuring impedance the systematic error occured, so we used the Quadratic Interpolation Self-calibration algorithm for calculation of the measured impedance. Calibration was applied on the absolute value of impedance. Calibration on the phase shift has not been done yet, since both input signals to GPD are highly disturbed with the noise, although they pass through a low-pass filter with cut-off frequency of 1 MHz. The superposed noise confuses GPD, so it cannot give the correct results. The relative error of impedance measurement after calibration ranges from -4.52 % to 5.98 % with mean value of -0.02 %.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.437
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.211
Teacher spread0.202 · 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 teacher head, not a consensus.

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

Citations14
Published2014
Admission routes1
Has abstractyes

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