ASSESSMENT OF THE SANITARY CONDITION OF THE MAIN FOREST-FORMING SPECIES IN THE ALUSHTA FORESTRY OF THE REPUBLIC OF CRIMEA
Bibliographic record
Abstract
The key problem of forestry is the deterioration of the sanitary condition of plantations, which de-termines the need for forest protection measures in the form of sanitary logging. The purpose of the study is to obtain new information about the quantitative and qualitative characteristics of forest ecosystems, to assess the sanitary condition of plantations of the main forest−forming species of the Republic of Crimea, as well as to analyze the growth and development of plantations in the Alushta forestry. In the course of the work, 4 sample areas were laid, on which the forestry and taxation in-dicators of the plantation were studied in detail and analyzed. The studied plantings are not inhabit-ed by harmful organisms and are not infected with diseases. The paper evaluates the current state and makes a forecast for the growth and development of stands of Oriental beech and Crimean pine after conducting selective sanitary logging (HRV). After the planned sanitary felling, dry–hardy trees will be completely removed, healthy trees will make up about 2% of the total stock, and weak-ened ones - about 60%. The weighted average value of the sanitary condition of the plantings is 2.35...2.49 points; all plantings will be classified as "weakened". It is recommended that timely sanitary and health measures be carried out in the form of selective sanitary logging of low intensity (10%) in the Alushta district forestry in quarter 21, allotment 24 and 26, as well as in the Zaprudensky district forestry in quarter 22, allotment 4. For intensive growth and development of planta-tions, as well as an increase in their growth, it should be carried out logging of care in Zaprudnenskoye district forestry in block 22, allotment 8.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".