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Record W1999344872 · doi:10.1029/2003gl018982

Ground‐based measurements of halogen oxides at the Hudson Bay by active longpath DOAS and passive MAX‐DOAS

2004· article· en· W1999344872 on OpenAlexaffabout
G. Hönninger, H.-G. Leser, Olatz San Sebastián, U. Platt

Bibliographic record

VenueGeophysical Research Letters · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsCanadian Meteorological and Oceanographic Society
Fundersnot available
KeywordsDifferential optical absorption spectroscopyBayOzone depletionOzoneHalogenEnvironmental scienceAtmospheric sciencesBromineLatitudeAbsorption (acoustics)MeteorologyChemistryGeologyOceanographyOpticsPhysicsGeodesy

Abstract

fetched live from OpenAlex

Intensive field measurements were carried out on the southeast coast of the Hudson Bay (55°N, 75°W) in spring 2001. The study focussed on reactive halogen chemistry and ozone/mercury depletion in the Hudson Bay region/Canadian lower Arctic. Several events of enhanced bromine oxide (BrO) coinciding with ozone depletion in the boundary layer (BL) were simultaneously measured by active longpath differential optical absorption spectroscopy (LP‐DOAS) and passive multi axis differential optical absorption spectroscopy (MAX‐DOAS). Significant differences in intensity and duration of ozone depletion events compared to high latitudes can be explained considering the daily alternation of daylight/nighttime which prevents complete ozone depletion within one day. First simultaneous measurements of active LP‐DOAS and passive MAX‐DOAS were carried out and compared. While LP‐DOAS monitored precise concentration values near the surface, MAX‐DOAS also captured BrO layers elevated from the surface which could not be seen by LP‐DOAS.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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 designObservational
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

Citations96
Published2004
Admission routes2
Has abstractyes

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