SCREENING ON SOME PERMANENT GRASSLANDS IN TIMIS COUNTY (WESTERN ROMANIA). CASE STUDY
Bibliographic record
Abstract
The grass of the grasslands is the most accessible source of food for herbivores during a significant period of a year. The knowledge of the floristic composition of grasslands reflects the current state and is an essential element in determining the load of animals. This paper is a case study and aims to inventory the species participating in the grass cover near some localities in Western Romania. Vegetation surveys were made in March, June and the first quarter of October. The study method by which the vegetation was determined is the linear method on the basis of which different indices could be calculated such as: specific frequency, biodiversity index, pastoral value. The obtained results led to the conclusion that the analyzed permanent meadows are classified as mediocre in terms of forage, the pastoral value expressing these aspects. Regarding the biodiversity of the analyzed grasslands, it is classified as medium and high in one of the cases. Based on the analysis of these results, respectively their correlation with the mode of intervention on these permanent grasslands, the possible evolutionary trends of the vegetation and its direction can be outlined in order to improve the economic value and the species richness.
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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 | 0.001 | 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) | 0.002 | 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".