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Record W2982277377 · doi:10.4095/215482

Digital summary database of permafrost and thermal conditions - Norman Wells pipeline study sites

2004· report· en· W2982277377 on OpenAlexaffabout
Sharon L. Smith, M M Burgess, D W Riseborough, Tara L. Coultish, J Chartrand

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPermafrostPipeline (software)DatabasePetroleum engineeringGeologyHydrology (agriculture)Computer scienceOceanographyGeotechnical engineeringOperating system

Abstract

fetched live from OpenAlex

The Norman Wells to Zama pipeline, located in northwestern Canada, is the first buried oil pipeline in the permafrost zone in Canada. During its construction in 1984-1985, the Canadian government and Enbridge pipelines collaborated in the establishment of a permafrost thermal monitoring program consisting of more than 20 long-term monitoring sites. This monitoring program was designed to investigate the impact of the pipeline construction and operation on permafrost and terrain conditions. Thermistor cables were installed both on and off the pipeline right-of-way to measure temperatures to depths of 20 metres. This report provides a summary ground temperature database from 1985-2001 for the Norman Wells pipeline corridor monitoring sites in digital relational database format. Maximum seasonal thaw depth for each year, interpolated from temperature profiles, is also provided. The ground surface settlement over time has been determined from field measurements and is presented in graphical format for each monitoring site.

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)0.001
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 score0.907
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.011
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1070.032

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 head0.017
GPT teacher head0.243
Teacher spread0.227 · 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

Citations23
Published2004
Admission routes2
Has abstractyes

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