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Record W7034197588

Stratospheric Odd Nitrogen: Measurements of HNO3, NO and O3 near 54°N in Winter

2010· article· en· W7034197588 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMixing ratioAltitude (triangle)StratospherePolarTroposphereOzone layerDaytimeAbundance (ecology)
DOInot available

Abstract

fetched live from OpenAlex

Data obtained during three stratospheric measurement campaigns from Cold Lake, Alberta (100.0°W, 54.4°N), in February 1977, 1978, and 1979 are presented. Altitude profiles of NO, HNO3, O3, CFM‐11, CFM‐12, and N2O and ground‐based total column measurements of NO2 were obtained and are compared with similar measurements made at 51°N in summer. The winter data demonstrate enhanced variability when compared with summer conditions, but in general in winter (1) there is a greater abundance of HNO3 and the stratospheric layer is thicker, (2) there is less nitric oxide particularly in the 18‐ to 28‐km region and the vertical distributions are characterized by strong mixing ratio gradients, and (3) the column abundance of NO2 is lower and exhibits a diurnal change qualitatively similar to that observed in summer. The difference between the summer and winter observations is not solely due to changes in photochemistry but requires consideration of stratospheric dynamics. We correlate the reduction in NO x in winter with the production of N2O5 in regions of little or no insolation followed by transport to Cold Lake. The unusual profiles are shown to result from air masses at different altitudes having either different origins, for example, polar or mid‐latitude, or different transit times from the source to the sampling point.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.015
GPT teacher head0.158
Teacher spread0.142 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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Same venueYork University Digital Library (York University)Same topicSpanish Linguistics and Language StudiesFrench-language works237,207