A Proposed Geoheritage Inventory System: Case Study of Isalo National Park, Madagascar
Bibliographic record
Abstract
Geological heritage inventory procedures and templates have been principally emerged from European countries. Each of these countries has developed its proper method of inventory based on its natural heritage, recognized on local and/or regional scales. Natural sites were mainly identified and characterized in a particular geological context, which is usually very unique, valuable and impressive; resulting in the protection of the sites. Madagascar is known internationally as a beautifully landscaped island, but the impressive sites were not cataloged. We carried out a series of field inventory of potential geological sites within the Isalo National Park in southern Madagascar. We invented several inventory sheets in order to record the most detailed information about the sites identified within the park. This is to aid in organizing the park and to establish a sustainable base for the creation of a geopark, and also they help us to build a database for geosites and their classifications. This article suggests a prototype model for inventorying intangible geosites, paleosites and geomorphosites. Our inventory sheets help to identify and to promote geological importance of any sites, not only for academia but also for other sectors such as tourism and conservation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".