An annotated checklist of amphibians in and around Dampa Tiger Reserve, Mizoram, India
Bibliographic record
Abstract
Amphibians are an integral part of the ecosystem and act as an ecological indicator. As several species are added to the list of threatened species every year due to loss of habitat, it is important to understand the role of unmanaged landscape for sustenance of amphibian diversity. In this study, 28 amphibian species were recorded from different modified habitat including 19 new records for Dampa Tiger Reserve (DTR) and its surrounding areas. Further, six species, Amolops indoburmanensis, Limnonectes khasianus, Microhyla mukhlesuri, M. mymensinghensis, Raorchestes rezakhani, and Sylvirana lacrima are new distribution records for the state of Mizoram and out of these, two species, Raorchestes rezakhani and Sylvirana lacrima, are new country records for India. Amongst the recorded species, four species are Data Deficient, two Vulnerable, 14 Least Concern, and eight species are not assessed as per the IUCN Red List. Within the core and buffer areas of DTR, we found that natural perennial stream, puddles, canals, natural ponds, fish ponds, roadside, primary forest, secondary forest, paddy fields, and human settlement areas are excellent microhabitats for amphibian population and need to be conserved for their rich ecological niches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".