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Record W2789938022 · doi:10.4095/261487

Baseline geotechnical and permafrost data from new field sites established in the Mackenzie corridor south of Norman Wells, Northwest Territories

2010· book· en· W2789938022 on OpenAlexaffabout
Sharon L. Smith, D W Riseborough, M Ednie, S Ye, J Chartrand

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPermafrostBaseline (sea)GeologyField (mathematics)Physical geographyGeotechnical engineeringArchaeologyGeographyOceanography

Abstract

fetched live from OpenAlex

A major field program was undertaken in February and March 2007 by the Geological Survey of Canada in order to address gaps in baseline environmental information in the Mackenzie Valley, south of Norman Wells, Northwest Territories. Sites were selected to represent a range of ground-thermal, terrain, and vegetation conditions. Drilling of boreholes to depths of 20 m yielded data for characterization of subsurface materials at 16 locations, including physical properties of soil and ground-ice conditions. Twenty boreholes were preserved and instrumented with temperature cables and the data acquired has enabled a preliminary characterization of the ground-thermal regime. Key baseline information was generated for a suite of representative terrain types that may be utilized in planning northern development and environmental impact assessment. Ongoing data collection from thermal monitoring sites will facilitate improved characterization of current permafrost conditions and change detection.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.987

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.002

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 head0.047
GPT teacher head0.249
Teacher spread0.202 · 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

Citations3
Published2010
Admission routes2
Has abstractyes

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