Geomorphometric analysis of cave ceiling channels mapped with 3-D terrestrial laser scanning
Bibliographic record
Abstract
Abstract. The change of hydrological conditions during the evolution of caves in carbonate rocks often results in a complex subterranean geomorphology, which comprises specific landforms such as ceiling channels, anastomosing half tubes, or speleothems organized vertically in different levels. Studying such complex environments traditionally requires tedious mapping; however, this is being replaced with terrestrial laser scanning technology. Laser scanning overcomes the problem of reaching high ceilings, providing new options to map underground landscapes with unprecedented level of detail and accuracy. The acquired point cloud can be handled conveniently with dedicated software, but applying traditional geomorphometry to analyse the cave surface is limited. This is because geomorphometry has been focused on parameterization and analysis of surficial terrain. The theoretical and methodological concept has been based on two-dimensional (2-D) scalar fields, which are sufficient for most cases of the surficial terrain. The terrain surface is modelled with a bivariate function of altitude (elevation) and represented by a raster digital elevation model. However, the cave is a 3-D entity; therefore, a different approach is required for geomorphometric analysis. In this paper, we demonstrate the benefits of high-resolution cave mapping and 3-D modelling to better understand the palaeohydrography of the Domica cave in Slovakia. This methodological approach adopted traditional geomorphometric methods in a unique manner and also new methods used in 3-D computer graphics, which can be applied to study other 3-D geomorphological forms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".