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Record W4406144532 · doi:10.1364/ao.546704

Calibration-free wavelength modulation spectroscopy approach for practical logging measurements of methane slip from natural gas engines

2025· article· en· W4406144532 on OpenAlexfundno aff
Nicolas A. F. Jaeger, Mhanna Mhanna, Jeremy Rochussen, Patrick Kirchen

Bibliographic record

VenueApplied Optics · 2025
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMethaneOpticsNatural gasWavelengthSpectroscopyCalibrationEnvironmental scienceRemote sensingMaterials sciencePhysicsGeologyEngineeringChemistry

Abstract

fetched live from OpenAlex

Natural gas (NG) is a potential substitute for diesel in engine applications because of its potential to reduce greenhouse gas and toxicant emissions. To maximize the benefits of NG, robust diagnostic methods are required to quantify concentration of unburned methane in the exhaust stream, without requiring frequent sensor recalibration. A wavelength modulation spectroscopy sensor has been developed to measure CH 4 slip from NG engines. The sensor uses the first-harmonic-normalized, second-harmonic (2 f /1 f ) processing method to perform long-duration, logging measurements at 20 Hz on an NG-powered marine vessel. Calibration-free 2 f /1 f measurements were shown to match calibrated 2 f /1 f measurements with an average error of 2.17% over the course of a 3 h sailing.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.294
Teacher spread0.267 · 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
Published2025
Admission routes1
Has abstractyes

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