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Record W2065763720 · doi:10.1029/2003gl017539

Long distance transport of pollen to Greenland

2003· article· en· W2065763720 on OpenAlexaboutno aff
Denis‐Didier Rousseau, Danielle Duzer, G. Cambon, Dominique Jolly, U. Poulsen, J. Ferrier, Patrick Schevin, Robert Gros

Bibliographic record

VenueGeophysical Research Letters · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersLamont-Doherty Earth Observatory, Columbia UniversityInstitut Polaire Français Paul Emile Victor
KeywordsPollenAir mass (solar energy)ArcticGroenlandiaGeologyAltitude (triangle)Greenland ice sheetPhysical geographyVegetation (pathology)ClimatologyOceanographyAtmospheric sciencesGeographyIce sheetBoundary layerEcology

Abstract

fetched live from OpenAlex

Four pollen traps were recently placed at coastal sites in East and West Greenland in order to assess long distance transport of pollen to the Arctic domain. By identifying potential vegetation source areas associated with air mass pathways we were able to produce the first detailed record of pollen transport from eastern North America to Narsarsuaq, southern Greenland. The record is based on observations and on a transport and dispersion model used to calculate back trajectories of the air masses. The evidence points to the pollen being transported northward by the air mass over Newfoundland and the Labrador Sea before reaching Narsarsuaq. At this point, the air mass was at an altitude of 3000 m. Deposition of pollen grains occurred with downward air movements associated with a 0.5 mm/h rain. The source areas for these pollen grains differ from those of dust and certain other aerosols that reach the summit of the Greenland Ice Sheet. The results demonstrate the need for continued maintenance and analysis of the Greenland pollen trap data in order to improve our understanding of atmospheric circulation and transport to high northern latitudes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.284
Teacher spread0.243 · 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 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

Citations73
Published2003
Admission routes1
Has abstractyes

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