Inventory, classification and genesis of the ground collapses in the groundwater body of the Western Mancha I
Bibliographic record
Abstract
This paper presents one of the first detailed studies about the ground collapses that have taken place in recent years in the central area of the groundwater body of the Western Mancha I, in the province of Ciudad Real. The main source of the collapses is the breakdown of the roof of the karst cavities, as a result of a rapid and unusual increase in the groundwater due to the widespread and intense rainfall, such as those that took place in the wet period (2009-2013). This brought about a washing of the karstic system, the movement of water through sinks and preferential channels, which had been dry for decades, as well as the dissolution of the chalky material itself. This ascent phase of the groundwater was preceded by a steady decrease in the piezometric levels, caused by prolonged drought and over-exploitation through pumping. To obtain an optimum knowledge of the area of study, important research has been done to localize, measure, and classify each of the collapses. Along with this, we have compiled, expanded, and updated the data of the piezometry, to a high level of detail. We have been able to distinguish four types of ground collapses: alluvial collapses, collapses in areas of dolines, lagoon collapses, and intermediate types of collapses. It is also evident that with the passage of years, the collapses that have been produced are of lesser dimensions. Finally, we have deduced the areas which have a greater susceptibility for new collapses, in places such as the river Guadiana, the lagoon areas, and some areas of dolines.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".