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Record W7124168100 · doi:10.5281/zenodo.18022925

A standardized permafrost ground temperature collection for Canada 2025

2025· article· W7124168100 on OpenAlexaffabout
Olivia Meier-Legault, Nicholas Brown, Stephan Gruber, Larry Adjun, Michel Allard, Alejandro Alvarez, Gerry Atatahak, Maude Auclair, Alex Bevington, Cable William, Olivia Carpino, A Castagner, Lin Chen, Alexandre Chiasson, Ryan Connon, Stéphanie Coulombe, Jeff W. Crompton, Derek Cronmiller, Gautier Davesne, Mason Dominico, Marc-André Ducharme, Joseph Young

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Language
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité du Québec à RimouskiEnvironment and Climate Change CanadaYukon UniversityWSP (Canada)Trent UniversityCenter for Northern StudiesMinistry of ForestsParks CanadaWilfrid Laurier UniversityUniversity of AlbertaUniversité de MontréalGovernment of Northwest TerritoriesGovernment of NunavutUniversité LavalUniversity of Northern British ColumbiaNatural Sciences and Engineering Research Council of CanadaUniversity of OttawaGeological Survey of CanadaCarleton University
Fundersnot available
KeywordsPermafrostClimate changeEctothermGlobal warmingAtmospheric temperature

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.053
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0180.011

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 head0.030
GPT teacher head0.243
Teacher spread0.213 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes2
Has abstractno

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicClimate change and permafrost→French-language works237,207→