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Record W2809062130 · doi:10.4095/289607

Seasonal surface displacement derived from InSAR, Pangnirtung, Nunavut

2012· report· en· W2809062130 on OpenAlexaffabout
N Short, A -M LeBlanc, W E Sladen, A -S Carbonneau, Michel Allard

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsInterferometric synthetic aperture radarDisplacement (psychology)GeodesyGeographyGeologySurface (topology)Remote sensingEnvironmental sciencePhysical geographyClimatologyMeteorologySynthetic aperture radarMathematicsGeometry

Abstract

fetched live from OpenAlex

This map shows the spatial distribution of the relative ground surface displacement between the major terrain units during one summer in the area of Pangnirtung. The ground displacement was derived using interferometric synthetic aperture radar (InSAR) data for the summer of 2011. Stable ground represents locations where either no vertical change was calculated or where displacement was within the expected range of error (± 0.5 cm). Very low, low, moderate, and high downward displacement represents surface lowering on the order of 0.5 to 2, 2 to 4.5, 4.5 to 8.5, and 8.5 to 10 cm, respectively. Upward displacement represents a surface rise of 0.5 to 3 cm. Areas of no data result from a loss of interferometric coherence. These are typically water and other relatively smooth surfaces from which there is no radar return, or where there has been significant ground surface disturbance and the radar returns cannot be correlated. The InSAR results correspond well with the expected displacement associated with the characteristics of the major terrain units. The displacement reflects seasonal settlement caused by thawing of ice in the active layer or in the near-surface permafrost.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.508

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.033
GPT teacher head0.258
Teacher spread0.224 · 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
Published2012
Admission routes2
Has abstractyes

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