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Record W1985402649 · doi:10.1139/e00-110

A paleoecological analysis of a southern permafrost peatland, Charlevoix, Quebec

2001· article· en· W1985402649 on OpenAlexafffundvenueabout
Claudia Zimmermann, Claude Lavoie

Bibliographic record

VenueCanadian Journal of Earth Sciences · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPeatMacrofossilPermafrostSubarctic climateGeologyBorealBogPhysical geographyDeforestation (computer science)TundraTaigaHolocenePaleontologyGeographyForestryArcticArchaeologyOceanography

Abstract

fetched live from OpenAlex

The southernmost site where permafrost has been located in the Quebec–Labrador peninsula is in a peatland on the subalpine summit of Lac des Cygnes Mountain (47°41'N, 70°36'W). Because of the thickness of its peat deposit, this site contains rich ecological information about the history of the peatland and its surrounding subalpine environment. We conducted a detailed macrofossil analysis to reconstruct the 6000-year history of the peatland. In general, the development of the Lac des Cygnes Mountain peatland has followed the classic succession of rich fen – poor fen – bog found in other peatlands in subarctic, boreal, and temperate environments. An abrupt decline in all tree macrofossils ca. 4000 BP suggests that a major deforestation event occurred on the summit of Lac des Cygnes Mountain. The exact cause of this deforestation event is unknown, but fire is a possible factor. The lack of absolute chronological resolution near the top of the macrofossil record precludes proper dating of permafrost inception, but the balance of evidence appears to indicate that the permafrost is modern.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.244
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2001
Admission routes4
Has abstractyes

Explore more

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