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Record W2982007605 · doi:10.4095/293701

Ground deformation observed near Cold Lake, Alberta, by RADARSAT-2 DInSAR during 2008-2013

2014· report· en· W2982007605 on OpenAlexaffabout
Sergey Samsonov

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsGeologyDeformation (meteorology)GeodesyOceanography

Abstract

fetched live from OpenAlex

Ground deformation in the Cold Lake, Alberta, region was measured with Differential Interferometric Synthetic Aperture Radar (DInSAR) from RADARSAT-2 imagery acquired during 2008-2013. Deformation maps presented here show subsidence and uplift produced during oil extraction. Typical values of ground deformation were in the range of and sometimes exceeding 10-30 cm over the 24 day satellite repeat period, which is more than 10 times faster than in other oil sands region that CCMEO has studied in collaboration with the Alberta Energy Regulator (AER). Significant deformation, both uplift and subsidence, was observed in regions where oil leaks were reported. These regions are shown as brown rectangles. This analysis may be significantly improved if ground based data such as, steam pressure, injection steam and oil extraction rates were used.

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: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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
GenreOther

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

Citations6
Published2014
Admission routes2
Has abstractyes

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