Bibliographic record
Abstract
Cyprus, an island located in the eastern Mediterranean Basin, was heavily forested prior to human settlement. Human influence since about 6000 BC has significantly changed the area and composition of the island's forests. Approximately 40% of the Island is presently occupied by forest, maquis and garigue vegetation. The dominant tree species in Cyprus' forests is Pinus brutia, which has been planted extensively on abandoned agricultural lands and areas burned by wildfire. P. brutia forests are subject to periodic wildfire episodes. In addition, young plantations are subject to defoliation by the pine processionary caterpillar, Thaumetopoea pityocampa (Lepidoptera: Pityocampidae), and older forests are subject to attack by several species of bark beetles (Coleoptera: Scolytidae). A policy of extensive planting of pines will, most likely, result in continued problems with wildfire, pine processionary caterpillar and bark beetles in the foreseeable future. Long-term measures to effectively manage these problems include examination of opportunities to plant alternative tree species and to manage the vegetation to increase the diversity of the Island's wildland ecosystems. Key words: Cyprus, forest protection, pine processionary caterpillar, bark beetles, wildfire
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 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 | 0.001 | 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) | 0.004 | 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".