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Record W2981358390 · doi:10.4095/306304

Ground thermal data collection along the Alaska Highway corridor (KP1559-1895), Yukon, summer 2016

2017· report· en· W2981358390 on OpenAlexaffabout
Sharon L. Smith, Antoni G. Lewkowicz, J Chartrand

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsEnvironmental scienceGeographyHydrology (agriculture)Physical geographyMeteorologyArchaeologyGeologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Ground temperature data were acquired in August 2016 from 14 boreholes along the northwestern section of the Alaska Highway corridor between kilometre post (KP) 1559 and KP 1895 near the Alaska border. Mean annual ground temperatures, determined at or near the zero annual amplitude depth, indicate that permafrost temperature in this section of the corridor is generally above -1°C with colder conditions near the Alaska border where permafrost can be as cold as -3°C. Temperatures measured in the upper 1-2 m indicate that permafrost is present at some sites where surface temperatures are above 0°C and where a sufficient thermal offset exists. These new data have extended existing records so that time series for these sites are 3 to 5 years long. Although mean annual air temperatures in the corridor have increased over the last few years, there is no consistent trend in ground temperature apparent in the short records. The information obtained helps characterize regional permafrost conditions in the southern Yukon and informs climate change impact assessments and adaptation planning.

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 score0.623
Threshold uncertainty score0.750

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.172
GPT teacher head0.315
Teacher spread0.143 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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