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Record W1975420654 · doi:10.1515/jag.2011.005

Deformation analysis of terrestrial monitoring observations on Turtle Mountain, Alberta

2011· article· en· W1975420654 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Applied Geodesy · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser University
KeywordsPoint cloudLaser scanningGeodesyDeformation monitoringDeformation (meteorology)Elevation (ballistics)GeologyIterative closest pointScannerPoint (geometry)Remote sensingGeographyGeometryLaserComputer scienceMathematicsComputer visionArtificial intelligencePhysicsOptics

Abstract

fetched live from OpenAlex

Abstract. Deformation monitoring has been car-ried out in two epochs on Turtle Mountain, Alberta, using a high-precision total station and a terrestrial laser scanner. From the total station observations, coordinates have been computed for seven signal-ized target points in a least-squares network adjust-ment. Then, a deformation analysis using a Multi-Parameter Transformation has been performed to derive movements between epochs. The two point clouds obtained with the laser scanner were regis-tered using the iterative closest point algorithm. Dif-ferences in elevation between the two point clouds were then derived for the entire scene. Results indi-cate a downward movement of South Peak, and no significant horizontal deformations were found.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.731
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.242
Teacher spread0.208 · 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