Bibliographic record
Abstract
Botanical gardens have an important role as ex-situ plant conservation areas, so the health condition of the botanical garden ecosystem must be considered so that it remains sustainable.However, currently not many studies have been carried out regarding the health of botanical garden ecosystems, especially in Lampung Province.Therefore, this research was conducted to assess and compare the health of ecosystems in all botanical gardens in Lampung Province.Measurement and analysis of research data was carried out using the Forest Health Monitoring (FHM) method based on ecological indicators in which the categories were bad, medium, and good.The research results obtained show that CL1 has a bad category with a value of 6.18; CL2 has a bad category with a value of 5.64; CL3 has a good category with a score of 7.89; and CL4 has a good category with a value of 7.61.Thus, the health condition of the ITERA Botanical Gardens and Liwa Botanical Gardens ecosystem has a final average score of 6.83 which is included in the medium category.It is important to always maintain and improve the health status of forests, considering that the existence of botanical gardens provides many benefits for the surrounding environment and society.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".