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Record W2625841213 · doi:10.1002/jqs.2958

Geochemical characterization (REE, Nd and Pb isotopes) of atmospheric mineral dust deposited in two maritime peat bogs from the St. Lawrence North Shore (eastern Canada)

2017· article· en· W2625841213 on OpenAlexaffabout
Steve Pratte, François De Vleeschouwer, Michelle Garneau

Bibliographic record

VenueJournal of Quaternary Science · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsOmbrotrophicPeatBogHoloceneGeologyIce coreDeposition (geology)PaleoclimatologyMineral dustOceanographyShorePhysical geographyEstuaryMarine isotope stageQuaternarySedimentClimate changeAerosolPaleontologyArchaeologyGeographyInterglacial

Abstract

fetched live from OpenAlex

ABSTRACT Dust deposited on two ombrotrophic peat bogs (Baie and IDH bogs) of the St. Lawrence Gulf and Estuary north shore (Quebec) was geochemically characterized using rare earth element (REE) concentrations, Nd and Pb isotopes along with particle grain size. Both cores display similar ɛNd values, which suggests either a common source or sources with similar signatures in both regions. Combining Nd isotope data with REE patterns and particle size allowed for better insights into the source of deposited dust and the inference of past environmental and climatic conditions in both regions. REEs, ɛNd and grain‐size distribution suggest that, over the last 2000 years, the Baie bog received more local dust due to increased local storminess in response to greater regional hydroclimatic variability. The same phenomenon occurred in the IDH bog since 620 cal a BP, i.e. during the Little Ice Age, where hydroclimatic and paleoecological changes have been previously documented. While the dust reconstructions and regional climatic records agree relatively well, the discrepancies between paleodust records highlight the complex and variable structure of late Holocene changes in paleoclimate and more particularly past dust deposition in eastern 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)0.001
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 score0.506
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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