MétaCan
Menu
Back to cohort
Record W2128933705 · doi:10.1149/05836.0049ecst

Sensitivity Analysis of Impedance Characteristics of a Laminar Flow-Based Fuel Cell

2014· article· en· W2128933705 on OpenAlex
Seyed Mohammad Rezaei Niya, Paul Barry, Mina Hoorfar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsElectrical impedanceLaminar flowDielectric spectroscopyVoltageSensitivity (control systems)Materials scienceOutput impedanceCurrent (fluid)Electronic circuitAnalytical Chemistry (journal)MechanicsElectrical engineeringChemistryElectronic engineeringElectrochemistryEngineeringPhysicsElectrodeChromatography

Abstract

fetched live from OpenAlex

The sensitivity of the impedance characteristics of a laminar flow-based fuel cell (LFFC) to the changes of the voltage, current and fuel concentration is analyzed using the electrochemical impedance spectroscopy (EIS) method. The impedance of the cell measured at different fuel concentrations and voltages is modeled using equivalent circuits. A t-test is performed on the values of the elements of the equivalent circuits estimated in successive voltages and fuel concentrations. As a result, intervals for the voltage, current and fuel concentration are identified in which the changes in the impedance characteristics of the cell cannot be distinguished statistically. These intervals, referred to as indifference intervals, show that the impedance characteristics of the cell is most sensitive to the changes in the voltage and current in the moderate frequency domains and least sensitive to the changes in the fuel concentration in the low frequency domains.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.327
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.205
Teacher spread0.201 · 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