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Record W2166366642 · doi:10.1016/j.yqres.2012.11.011

Evidence for large-amplitude biome and climate changes in Atlantic Canada during the last interglacial and mid-Wisconsinan periods

2012· article· en· W2166366642 on OpenAlexfundaboutno aff
Bianca Fréchette, Anne de Vernal

Bibliographic record

VenueQuaternary Research · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologies
KeywordsInterglacialTundraTaigaBiomeGeologyClimatologyBorealClimate changeSubarctic climateDeciduousGlacial periodPhysical geographyTemperate deciduous forestArcticOceanographyGeographyEcologyGeomorphologyPaleontologyForestryEcosystem

Abstract

fetched live from OpenAlex

Abstract Last interglacial and mid Wisconsinan pollen data from sedimentary sequences of Cape Breton Island in Atlantic Canada were analyzed to reconstruct biome and climate conditions. Our results show warm and humid climate with mean annual temperature 6–7°C higher than today, up to 15–20% more sunshine and significantly longer growing season that fostered growth of temperate trees during the optimum of the last interglacial. The northern limit of the deciduous forest biome was then about 500 km north of its modern limit. Towards the end of the interglacial the deciduous forest was replaced by conifer/hardwood forest and boreal forest. Climate was then similar to modern. The transition from interglacial to glacial was marked by a change towards coniferous forest related to colder and dryer conditions. During the mid Wisconsinan, the development of forest tundra to boreal forest reflects migration of the Arctic Front and significant cooling with mean annual temperature anomalies of − 8 to − 12°C. The overall time series reflect large amplitude climate changes that point to high sensitivity of the southeastern Canadian margins, likely as a response to latitudinal shifts of the Gulf Stream and variable strength of the Labrador Current together with changes in large-scale atmospheric circulation pattern.

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)0.003
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 score0.847
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.103
GPT teacher head0.353
Teacher spread0.249 · 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

Citations15
Published2012
Admission routes2
Has abstractyes

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