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Record W2093654057 · doi:10.1117/12.830476

Preliminary tropospheric ozone DIAL, water vapour, and aerosol lidar measurements during ARC-IONS

2009· article· en· W2093654057 on OpenAlexaffabout
K. B. Strawbridge, B. Firanski

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsLidarEnvironmental scienceTroposphereTropopauseOzoneAerosolTropospheric ozoneWind profilerRemote sensingWater vaporMeteorologyDialAtmospheric sciencesRadarGeologyPhysicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

A new lidar instrument, dubbed AeRO (Aerosol Raman Ozone) Lidar, is being developed at Environment Canada's Centre For Atmospheric Research Experiments (CARE). The new system will use three lasers to simultaneously measure ozone, water vapour and aerosol profiles (including extinction) from near ground to the tropopause. The main thrust will focus on understanding Air Quality within the airshed with the capability of looking at Stratospheric Tropospheric Exchange (STE) processes to determine the magnitude and frequency of such events leading to elevated levels of tropospheric ozone. In addition a wind profiler through a partnership with University of Western Ontario will soon be deployed to CARE to provide complementary observations of the tropopause. The lidar participated in the ARC-IONS field campaign during April and July of 2008. During the field campaign, daily ozonesondes were released to further compliment the lidar measurements. Details of the system design and preliminary results from the lidar measurements will be presented.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.008
GPT teacher head0.197
Teacher spread0.189 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE→Same topicAtmospheric and Environmental Gas Dynamics→French-language works237,207→