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Record W2095452762 · doi:10.1016/j.yqres.2005.08.021

Paleoenvironmental records of water level and climatic changes from the middle to late holocene at a Lake Erie coastal wetland, Ontario, Canada

2005· article· en· W2095452762 on OpenAlexaffabout
Sarah A. Finkelstein, Anthony M. J. Davis

Bibliographic record

VenueQuaternary Research · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPeatHoloceneWetlandWater levelGeologyBogPhysical geographyShoreMarine transgressionMarshDiatomMacrofossilChronologyOceanographySedimentologyGeographyArchaeologyGeomorphologyPaleontologyEcologyStructural basinCartography

Abstract

fetched live from OpenAlex

Abstract Pollen and diatom assemblages, and peat stratigraphies, from a coastal wetland on the northern shore of Lake Erie were used to analyze water level and climatic changes since the middle Holocene and their effects on wetland plant communities. Peat deposition began 4700 cal yr B.P. during the Nipissing II transgression, which was driven by isostatic rebound. At that time, a diatom-rich wild rice marsh existed at the site. Water level dropped at the end of the Nipissing rise at least 2 m within 200 yr, leading to the development of shallower-water plant communities and an environment too dry for most diatoms to persist. The sharp decline in water level was probably driven primarily by outlet incision, but climate likely played some role. The paleoecological records provide evidence for post-Nipissing century-scale transgressions occurring around 2300, 1160, 700 and 450 cal yr B.P. The chronology for these transgressions correlates with other studies from the region and implies climatic forcing. Peat inception in shallow sloughs across part of the study area around 700 cal yr B.P. coincides with the Little Ice Age. These records, considered alongside others from the region, suggest that the Little Ice Age may have resulted in a wetter climate across the eastern Great Lakes region.

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 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 score0.159
Threshold uncertainty score0.987

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0140.000

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 head0.088
GPT teacher head0.262
Teacher spread0.175 · 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

Citations35
Published2005
Admission routes2
Has abstractyes

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