Bibliographic record
Abstract
Eria meghasaniensis is one of the endemic Orchids of Odisha with a single population of nearly 150 plants found in Simlipal area of Odisha. It needs immediate measures to ensure its recovery and survival. On examination of various provisions of the Wildlife (Protection) Act, 1972 and the Odisha Forest Act, 1972, it is seen that they are not very helpful in rehabilitation of such species. Section 38 of the Biological Diversity Act, 2002, takes care of such species. However, the mechanism in place to implement this section to its full scope needs strengthening. For this purpose the Endangered Species Act (ESA) of USA and Species At Risk Act (SARA) of Canada were examined and it is found that they have good provisions to focus on rehabilitation of species at risk and to save them from extinction. It is highly required to develop a robust mechanism to implement the provisions of section 38 of the Biological Diversity Act, 2002, by using acts like ESA and SARA as guiding features. By developing an open and transparent process, based on scientific data available, with an actionable and time bound recovery plan and with the involvement of all stakeholders, it may be possible to save species like Eria meghasaniensis from extinction.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".