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Record W7083190740 · doi:10.5281/zenodo.17122071

Protecting Permafrost: Addressing the climate threat of Arctic thaw

2025· report· en· W7083190740 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicSoil and Environmental Studies
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsPermafrostArcticClimate changeGovernment (linguistics)Greenhouse gasThe arcticGlobal warming

Abstract

fetched live from OpenAlex

Protecting Permafrost: Addressing the Climate Threat of Arctic Thaw examines the significant climate threat posed by Arctic permafrost thaw. Climate heating is causing permafrost to thaw, leading to the release of heat-trapping gases like carbon dioxide and methane, which in turn accelerates climate change. The report assesses 13 potential interventions to slow or stop thaw and reduce emissions, with three being ready for deployment: wildfire management, caribou herding, and conservation or restoration of peatlands and wetlands. The report emphasizes the need for a comprehensive approach, including improving scientific understanding, gathering better data, developing permafrost thaw models, and creating governance frameworks. It recommends that the Canadian federal government establish a permafrost thaw mitigation task force to develop a national strategy, leveraging Canada's scientific capabilities and international collaborations to address this global challenge.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.921
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.122
GPT teacher head0.274
Teacher spread0.152 · 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