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Record W4250779922 · doi:10.1080/15428110308984863

Exposure to Diesel Exhaust Emissions on Board Locomotives

2003· article· en· W4250779922 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAIHA Journal · 2003
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsEmployment and Social Development Canada
FundersTransport Canada
KeywordsEnvironmental scienceCarbon dioxideDiesel fuelAtmospheric sciencesThreshold limit valueMean valueAnimal scienceMeteorologyStatisticsToxicologyMathematicsAutomotive engineeringEngineeringChemistryMedicinePhysicsEnvironmental health

Abstract

fetched live from OpenAlex

Measurements of diesel exhaust emissions (DEEs) were taken in the cabs of leading and trailing locomotives on 48 runs, under winter and summer conditions, on 9 different routes. The cab windows were kept open during the summer runs and closed during the winter runs. The average measurement duration was 9.5 hours. There was virtually no exposure to DEEs in the lead locomotives during winter or summer and very little in the trailing locomotives during winter. The average elemental carbon (EC) concentration in the trailing units of the summer trials was greater than or equal to the proposed American Conference of Governmental Industrial Hygienists' threshold limit value/time-weighted average of 20 µg/m3 on 26% of the runs, and was greater than or equal to 10 µg/m3 on 63%. The concentrations of the gaseous components (nitric oxide, nitrogen dioxide, and carbon monoxide) were from 10 to 20 times below their respective threshold limit values. Mean EC concentration was 2.9 µg/m3 (detection limit 2 µg/m3) during the winter runs and 17.1 µg/m3 during summer. DEEs appeared to be fairly uniformly distributed in the trailing cabs. Configuration of the locomotives had a major impact on EC concentration, with the mean concentration being nearly three times higher in the forward–backward mode than in the forward–forward mode. Descriptive statistics such as means, medians, standard deviations, and so forth, are provided. Various types of statistical comparisons are reported. Recommendations for controlling exposure are made.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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