MétaCan
Menu
Back to cohort
Record W3211251005 · doi:10.1017/qua.2021.56

The signal of climate changes over the last two millennia in the Gulf of St. Lawrence, eastern Canada

2021· article· en· W3211251005 on OpenAlexaffabout
Xiner Wu, Anne de Vernal, Bianca Fréchette, Matthias Moros, Kerstin Perner

Bibliographic record

VenueQuaternary Research · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsOceanographyPollenGeologyDinocystPalynologyClimate changeArcticHoloceneAbrupt climate changeClimatologyAlkenonePhysical geographyGlobal warmingEffects of global warmingGeographyEcology

Abstract

fetched live from OpenAlex

Abstract Climate changes over the past two millennia in the central part of the Gulf of St. Lawrence are documented in this paper with the aim of determining and understanding the natural climate variability and the impact of anthropogenic forcing at a regional scale. The palynological content (dinocysts, pollen, and spores) of the composite marine sediment core MSM46-03 collected in the Laurentian Channel was used to reconstruct oceanographic and climatic changes with a multidecadal temporal resolution. Sea-surface conditions, including summer salinity and temperature, sea-ice cover, and primary productivity, were reconstructed from dinocyst assemblages. Results revealed a remarkable cooling trend of about 4°C after 1230 cal yr BP (720 CE) and a culmination with a cold pulse dated to 170–40 cal yr BP (1780–1910 CE), which likely corresponds to the regional signal of the Little Ice Age. This cold interval was followed by a rapid warming of about 3°C. In the pollen assemblages, the decrease of Pinus abundance over the past 1700 yr suggests changes in wind regimes, likely resulting from increased southerly incursions of cold and dry Arctic air masses into southeastern 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)0.004
metaresearch head score (Gemma)0.000
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 score0.718
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.314
Teacher spread0.262 · 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

Citations7
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueQuaternary ResearchSame topicGeology and Paleoclimatology ResearchFrench-language works237,207