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Record W1942976897 · doi:10.1002/ppp.1735

The Impact of Permafrost Disturbances and Sediment Loading on the Limnological Characteristics of Two High Arctic Lakes

2012· article· en· W1942976897 on OpenAlexafffund
Hilary A. Dugan, Scott F. Lamoureux, Ted G. Lewis, Melissa J. Lafrenière

Bibliographic record

VenuePermafrost and Periglacial Processes · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsQueen's University
FundersOffice of International Science and EngineeringNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostSedimentWatershedArcticHydrology (agriculture)Disturbance (geology)GeologyActive layerLimnologyEnvironmental scienceOceanographyGeomorphologyGeotechnical engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

ABSTRACT The physical and chemical characteristics of two High Arctic lakes were investigated at the Cape Bounty Arctic Watershed Observatory on Melville Island, in response to large active‐layer detachments generated by extreme summer temperatures in 2007. In the two years following the permafrost disturbances, there was an elevated loading of total dissolved solids into both lakes, but no concomitant increase in suspended sediment levels. The physical dynamics of one lake were significantly altered by an internal sediment input, which was not directly related to watershed processes. The results indicate that localised permafrost disturbance in the watersheds resulted in changes to chemical conditions in these relatively deep, large lakes, while increased sediment transport from disturbances did not have a sustained impact. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.001
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 score0.096
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.270
Teacher spread0.239 · 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

Citations37
Published2012
Admission routes2
Has abstractyes

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