A WebGIS tool to support forest management at regional and local scale
Bibliographic record
Abstract
One of the most important obstacles for taking advantage of forest resources in the Italian Alps is represented by the high level of private properties fragmentation and by their small size. Thus, there is an urgent need for tools to support single or multi-forest owners to gain reliable and updated information on their forest stands so that the proper silvicultural activities following all the existing regulations can be adopted. The present research was aimed at promoting a shared management of small private forest properties in the mountainous area of Friuli Venezia Giulia (NE Italy) through the implementation of a new WebGIS tool to support forest decisions and management at different spatial scales. This new tool was developed updating and merging together different available information sources (e.g., tree species composition, the presence of protected areas, forest roads, etc.) with ad-hoc elaborated layers (e.g., standing volume, annual increment of volume, forest accessibility, etc.), also elaborating a cost analysis related to the different possible harvesting methods. The tool allows queries at the level of either a single or a group of cadastral parcels to obtain data in a format, which can be used for filling in the planning document requested by the regional authorities.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".