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Record W3209626128 · doi:10.1061/9780784483589.001

Long-Term (2000–2017) Response of Lake-Bottom Temperatures and Talik Configuration to Changes in Climate at Two Adjacent Tundra Lakes, Western Arctic Coast, Canada

2021· article· en· W3209626128 on OpenAlexaffabout
Trevor Andersen, Patrick A. Jardine, C. R. Burn

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsCarleton University
Fundersnot available
KeywordsTundraPermafrostTerrace (agriculture)ShoreArcticPhysical geographyGeologyClimate changeOceanographyEnvironmental scienceAtmospheric sciencesClimatologyGeography

Abstract

fetched live from OpenAlex

Lakes, commonly underlain by taliks, are principal agents of disturbance to permafrost. We have measured lake-bottom temperatures with submerged loggers on near-shore terraces and in deep central pools at two tundra lakes on Richards Island, NT, to determine inter-annual lake thermal responses to climate variation. We have modelled associated potential adjustments in talik geometry. In 2000–17, annual mean temperatures varied between -5.7 and 2.8°C for terraces and 1.1 and 4.5°C for pools. Permafrost in the terraces is warmer than surrounding the lakes: talik configuration varies with horizontal terrace extent and terrace and pool temperatures. The talik break-through depth declines as terrace size increases. Using the four warmest and coldest years as an analogue for climate change—an adjustment that may occur this century—the increase in talik depth may be up to 100 m, but it may take millennia for talik geometry to reach equilibrium.

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 score0.220
Threshold uncertainty score0.442

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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