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Record W2019990548 · doi:10.1029/1999jd901180

Atmospheric organochlorine pesticides in the western Canadian Arctic: Evidence of transpacific transport

2000· article· en· W2019990548 on OpenAlexaboutno aff
Robert E. Bailey, Leonard A. Barrie, Crispin Halsall, Phil Fellin, Derek C. G. Muir

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsChlordaneLindaneEnvironmental sciencePesticideHeptachlorArcticEnvironmental chemistryAtmospheric sciencesPhysical geographyOceanographyOrganochlorine pesticideGeographyEcologyChemistryGeologyBiology

Abstract

fetched live from OpenAlex

Concentrations of hexachlorocyclohexanes (HCHs), chlordane, and dichlorodiphenyltrichloroethane (DDT) were measured in ambient air samples on a weekly basis between December 1992 and January 1995 at Tagish Yukon, Canada. In winter, unusually high air concentrations of HCHs, DDT, and chlordanes at Tagish were predominantly influenced by transpacific long‐range atmospheric transport from eastern Asia that generally occurred within 5 days. HCH and heptachlor epoxide concentrations were correlated with the time that air spent over eastern Asia prior to arrival at Tagish. Chlordane and DDT, which also increase with transpacific transport, do not show a correlation with the time the upwind airshed included Asia as the composition of these pesticides in the atmosphere is affected by differences in usage patterns, application methods, variable composition of parent pesticides and metabolites in the soil, and rates of volatilization. Air masses originating from North America had the highest concentrations of HCHs and chlordanes when the 5‐day upwind airshed included the western United States. Concentrations of HCHs may also be influenced by lindane usage in Canada.

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)0.002
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.034
GPT teacher head0.308
Teacher spread0.275 · 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 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

Citations140
Published2000
Admission routes1
Has abstractyes

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