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Record W7100725294

Policy Implications of Warming Permafrost Policy Implications of Warming PermafrostExecutive Summary

2013· article· en· W7100725294 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMathematics, Computing, and Information Processing
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostActive layerSnowNorthern HemisphereAir temperatureThermokarstSnowpackCryosphere
DOInot available

Abstract

fetched live from OpenAlex

Permafrost is perennially frozen ground occurring in about 24 % of the exposed land surface in the Northern Hemisphere. The distribution of permafrost is controlled by air temperature and, to a lesser extent, by snow depth, vegetation, orientation to the sun and soil properties. Any location with annual average air temperatures below freezing can potentially form permafrost. Snow is an effective insulator and modulates the effect of air temperature, resulting in permafrost temperatures up to 6°C higher than the local mean annual air temperature. Most of the current permafrost formed during or since the last ice age and can extend down to depths of more than 700 meters in parts of northern Siberia and Canada. Permafrost includes the contents of the ground before it was frozen, such as bedrock, gravel, silt and organic material. Permafrost often contains large lenses, layers and wedges of pure ice that grow over many years as a result of annual freezing and thawing of the surface soil layer. About 24 % of the northern hemisphere land surface contains permafrost, divided into zones of continuous, discontinuous, sporadic and isolated patches of permafrost, depending on how much of the land area contains permafrost. Two global networks monitor permafrost status: the Thermal State of Permafrost (TSP) network measures permafrost temperature at various depths in 860 boreholes, and the Circumpolar Active Layer Monitoring (CALM) network measures the thickness of the active layer at 260 sites. The active layer thickness is the maximum surface thaw depth

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)0.002
metaresearch head score (Gemma)0.006
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: Review · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0370.003

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 head0.019
GPT teacher head0.285
Teacher spread0.266 · 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
GenreReview

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
Published2013
Admission routes1
Has abstractyes

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