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Record W2548186806

Climate change and water availability over the last two millennia in Little Raleigh Lake, northwestern Ontario.

2011· article· en· W2548186806 on OpenAlexaboutno aff
Susan Ma

Bibliographic record

VenueQSpace (Queen's University Library) · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeGeographyPhysical geographyOceanographyEnvironmental scienceHydrology (agriculture)Geology
DOInot available

Abstract

fetched live from OpenAlex

The Winnipeg River Drainage Basin (WRDB), located in the boreal forest region of Canada, is a pivotal region of focus for the assessment of water availability to determine susceptibility to drought in the past.To date, there have been relatively few paleolimnological studies focusing on how lake levels have changed in the past and whether these changes have been synchronous in the WRDB.This study investigates temporal patterns in effective moisture from Little Raleigh Lake over the last two millennia.Analyses are based on diatoms from two near-shore sediment cores from different locations and water depth in Little Raleigh Lake.Changes in diatom assemblages are used to reconstruct quantitative estimates of effective moisture in the past through the calibration of a diatom-inferred depth model developed from diatom assemblages in surficial sediments along a depth transect in Little Raleigh Lake.Declines of ~1-3m occurred during the late Holocene, with prolonged periods of aridity consistent with the timing of the Medieval Climate Anamoly (~950-1250AD) and the Little Ice Age (~1650-1750AD).The nearshore core retrieved closer to the present-day ecotone between the benthic and planktonic diatom assemblages was more sensitive to tracking water level changes in the lake than the deeper core.Conditions during the last two millennia can be used for the assessment of water availability in the past, and may offer insight on future conditions under increasing temperatures.

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)0.000
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 score0.583
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.021
GPT teacher head0.161
Teacher spread0.140 · 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

Citations1
Published2011
Admission routes1
Has abstractyes

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