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Permafrost degradation under expanding thermokarst lakes, Yukon, Canada

2014· article· en· W2285662228 on OpenAlexaboutno aff
Pascale Roy‐Léveillée

Bibliographic record

VenueFigshare · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsThermokarstPermafrostPhysical geographyDegradation (telecommunications)GeologyEnvironmental scienceHydrology (agriculture)Earth scienceGeographyOceanographyComputer scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

This poster presents patterns of permafrost degradation under lakes with eroding shorelines in Old Crow Flats, Northern Yukon. Old Crow Flats is an arctic peatland in the continuous permafrost zone. Two shorelines with contrasting rates of recession, bank morphology, and vegetation cover were studied in the field. Depth to permafrost beneath the lakes was measured by jet drilling. Permafrost degradation occurs under very shallow water. Snow drifting on the ice surface affects patterns of permafrost degradation despite minimal effect on mean annual lake bottom temperatures. This poster was presented at the IPY 2012: From Knowledge to Action Conference, held April 22-27, 2012, in Montreal, QC, Canada. http://www.ipy2012montreal.ca/index.php Citation of conference poster: Roy-Léveillée P, Burn CR. (2012) Talik geometry and permafrost degradation under thermokarst lakes in the Old Crow Flats, Yukon Territory, Canada. IPY 2012: From Knowledge to Action, April 22-27, 2012, Montreal, QC.

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 score0.029
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.051
GPT teacher head0.229
Teacher spread0.177 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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