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Record W2038139585 · doi:10.1149/05012.0295ecst

Zirconia-Based Electrochemical Oxygen Sensor for Accurately Determining Water Vapor Concentration

2013· article· en· W2038139585 on OpenAlexaff
R.E. Soltis

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsFord Motor Company (Canada)
Fundersnot available
KeywordsOxygen sensorCubic zirconiaWater vaporRelative humidityOxygenHumidityMaterials scienceAnalytical Chemistry (journal)Degree (music)ElectrochemistryLimiting oxygen concentrationChemistryElectrodeComposite materialEnvironmental chemistryThermodynamicsAcousticsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

By varying the control voltages of commercially available zirconia-based automotive exhaust gas oxygen sensors, other oxygen-containing molecules such as H2O and CO2 can be measured. Typical water concentration sensors that measure relative humidity via swelling of certain polymers have a narrow temperature range of operation (typically < 120{degree sign}C) and limited accuracy of about {plus minus} 0.4% absolute. Initial measurements with modified zirconia oxygen sensors, both in the laboratory and on engine dynamometers, have shown that water vapor concentration in a gas stream can be measured accurately to {plus minus} 0.1% over the range from 0-20 vol% H2O at temperatures up to 800{degree sign}C.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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