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Record W2038508132 · doi:10.1029/2004jd005187

Development and evaluation of a sampling system to determine gaseous Mercury fluxes using an aerodynamic micrometeorological gradient method

2005· article· en· W2038508132 on OpenAlexaff
Grant C. Edwards, Pat E. Rasmussen, W. H. Schroeder, Danielle Wallace, L. Halfpenny‐Mitchell, G. M. Dias, R. J. Kemp, Sandra Ausma

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsMinistry of the Environment, Conservation and ParksRowan Williams Davies & Irwin (Canada)Mohawk CollegeAgriculture and Agri-Food CanadaUniversity of GuelphHealth Canada
Fundersnot available
KeywordsFlux (metallurgy)Environmental scienceMercury (programming language)Sampling (signal processing)Potential gradientAtmospheric sciencesAerodynamicsGradient methodMeteorologyPhysicsChemistryMechanicsOptics

Abstract

fetched live from OpenAlex

An aerodynamic gradient micrometeorological approach to the measurement of total gaseous mercury (TGM) flux has been developed. This method has been applied in many field studies for the characterization of TGM flux from various mercuriferous substrates. The resolution of the gradient method depends on the sampling systems characteristics and has been demonstrated to be on the order of 0.01 ± 0.01 ng Hg m −3 or better. The method is best suited to measuring high‐emitting sites such as studied here. The TGM flux resolution is based on the gradient resolution and depends on the site characteristics and the atmospheric condition. For a typical friction velocity u * of 0.1 m s −1 and gradient intake heights of 0.15 and 0.4 m the method can resolve a TGM flux on the order of 1.5 ng m −2 h −1 . The system can be configured for two‐level or multilevel sampling, as needed. The method compares well with other micrometeorological methods as demonstrated during the Nevada storms intercomparison study. The micrometeorological method is shown to compare well with chamber techniques under comparable 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 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)0.004
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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)0.0000.000

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 head0.080
GPT teacher head0.363
Teacher spread0.283 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations63
Published2005
Admission routes1
Has abstractyes

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