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Record W1482423444 · doi:10.1109/intlec.1994.396644

Evaluation of conductance and impedance testing on VRLA batteries for the Stenter Operating Companies

2002· article· en· W1482423444 on OpenAlexaff
R. Heron, A.A. McFadden, J. Dunn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsConductanceElectrical impedanceSet (abstract data type)CutoffFocused Impedance MeasurementComputer scienceVariance (accounting)Lead–acid batteryReliability engineeringStatisticsElectrical engineeringMathematicsEngineeringBattery (electricity)PhysicsThermodynamics

Abstract

fetched live from OpenAlex

Conductance and impedance testing have been proposed in recent years as possible methods of assessing the condition of VRLA (valve regulated Pb-acid) batteries. This paper presents extensive data gathered and analyses it in a number of ways. It includes studying the variance in measurements, correlation with capacity, calculation of 80% cutoff values, box score analysis, investigation of historic trends and intertest-set comparisons. Although conductance and impedance were found to be partly related to capacity, a number of variables and sources of error were identified which significantly affect the accuracy of results. Conductance and impedance testing were found to be a useful aid in identifying good and bad batteries. A number of proposed procedures are suggested for making effective use of these tools.>

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)0.002
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.166
GPT teacher head0.332
Teacher spread0.166 · 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 designObservational
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

Citations16
Published2002
Admission routes1
Has abstractyes

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