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Record W4384666136 · doi:10.1029/2023jf007262

Widespread Permafrost Degradation and Thaw Subsidence in Northwest Canada

2023· article· en· W4384666136 on OpenAlexaffabout
H B O'Neill, Sharon L. Smith, C. R. Burn, C Duchesne, Yu Zhang

Bibliographic record

VenueJournal of Geophysical Research Earth Surface · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsCarleton UniversityGeological Survey of CanadaNatural Resources Canada
Fundersnot available
KeywordsPermafrostPhysical geographyActive layerGeologyGroundwater-related subsidenceSubsidenceEnvironmental scienceHydrology (agriculture)GeomorphologyGeotechnical engineeringOceanographyGeographyLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract Long‐term (1991–2018) thaw tube measurements highlight widespread permafrost thaw and ground surface (GS) subsidence over a large portion of northwest Canada. Statistically significant positive trends in thaw penetration (TP), measured with respect to a fixed datum, were observed at 18 of 28 sites with data that span three decades at a median rate of 0.8 cm a−1. This rate implies thawing of about 22 cm of permafrost over the study period. Similarly significant trends in GS subsidence occurred at 21 of 28 sites, at a median rate of 0.4 cm a−1. In contrast with TP and GS elevation, long‐term trends in active layer thickness (ALT) were less consistent, with 10 of 28 sites having statistically significant trends indicating increasing ALT (median rate: 0.6 cm a−1), and 7 sites having trends indicating decrease in ALT (median: 0.3 cm a−1). The ALT measurements underestimated the thawing of ice‐rich permafrost due to GS subsidence. Sites with high rates of thaw had relatively warm permafrost, deep snow cover, and poor drainage. Masking of ice‐rich permafrost degradation by ALT measurements has important implications for modeling permafrost thaw and climate change reporting. Accurate simulation of ice‐rich permafrost thaw is conceivable for sites where conditions are well‐defined. However, the prediction of subsidence and TP at regional or broader scales is only possible in general terms due to variation in surface conditions and ground ice content. Trends in TP and GS subsidence more accurately characterize ice‐rich permafrost degradation than trends in ALT.

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 score0.019
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.075
GPT teacher head0.314
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

Citations70
Published2023
Admission routes2
Has abstractyes

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