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Record W1991076971 · doi:10.1063/1.1488680

Characterization and application of an externally mounted catalytic converter for aircraft measurements of NOy

2002· article· en· W1991076971 on OpenAlexaff
L. Lange, Hubertus Fischer, Uwe Parchatka, C. Gurk, T. Zenker, G. W. Harris

Bibliographic record

VenueReview of Scientific Instruments · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsYork University
FundersMax-Planck-GesellschaftTechnische Universiteit DelftEuropean Commission
KeywordsTroposphereStratosphereFuselageEnvironmental scienceReactive nitrogenReproducibilityNitrogen oxideAerospace engineeringAtmospheric sciencesMeteorologyNitrogenMaterials scienceRemote sensingNuclear engineeringNOxPhysicsGeologyChemistryCombustion

Abstract

fetched live from OpenAlex

A novel design for an airborne NOy converter was implemented, characterized in the laboratory, and used extensively for in situ tropospheric and stratospheric measurements of total reactive nitrogen (NOy). During field deployments, the converter is mounted outside the aircraft fuselage, avoiding the need for an inlet line. In flight, the converter can be calibrated by the addition of standard gases close to the sample inlet, compensating for any changes in the instrument sensitivity caused by changing operating conditions. The system has been used successfully during several Stratosphere Troposphere Experiments by Aircraft Measurements campaigns in the lowermost stratosphere and upper troposphere for the measurement of total reactive nitrogen. The detection limit of the system is approximately 100 pptv for 10 s integrated data (2σ). The precision, deduced from the reproducibility of the in-flight calibrations, is 7% and the accuracy is about 30%. Laboratory studies demonstrate that interference from HCN, NH3, and CH3CN is negligible for background conditions.

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 integrity0.0000.000
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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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

Citations9
Published2002
Admission routes1
Has abstractyes

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