Characterization and monitoring of the Åknes landslide using terrestrial laser scanning
Bibliographic record
Abstract
Le scanner laser terrestre (SLT) de longue portée est un outil puissant pour la surveillance de mouvements de versant, puisqu'il fournit une image 3D de haute résolution de la topographie.Cet article décrit de possibles analyses d'images SLT de pentes rocheuses instables.Les images SLT sont utilisées pour l'analyse structurale de l'escarpement principal vertical et inaccessible du glissement rocheux d'Åknes en Norvège, incluant la détermination des jeux de discontinuités et des axes de plis.Des déplacements déterminés à l'aide de séries temporelles de données SLT contiennent non seulement des informations sur la vitesse et la direction de déplacement (6-7 cm/an vers 185° avec un plongement de 55°), mais aussi sur des composants rotationnels, tels que le basculement (vers 327° par 0.03°).Un possible modèle de l'instabilité explique les déplacements transrationnels et rotationnels mesurés par une combinaison de glissement plan, tassement et basculement.ABSTRACT Long-range terrestrial laser scanning (TLS) is a powerful tool to monitor slope movements, since it provides a high-resolution 3D image of the topography.This article presents a review of the possible analyses of TLS images of instable rock slopes.The TLS images are used for the structural analysis of the steep, inaccessible main scar of the Åknes rockslide in Norway, including assessment of the discontinuity sets and fold axes.Displacements determined by a time-series analysis of TLS data provide information on movement velocities and directions (6-7 cm/year towards 185° with a plunge of 55°), as well as rotational components, like toppling (towards 327° by 0.03°).A possible instability model explains the measured translational and rotational displacements by a combination of planar sliding, sackung and toppling towards the opened graben structure.1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".