Mitochondrial DNA diversity in wild gaur (<i>Bos gaurus gaurus</i>): evidence from extant and historical samples
Bibliographic record
Abstract
Bos gaurus gaurus commonly called as gaur is a wild bovid species inhabiting South and Southeast Asia and attained vulnerable status in India. In this study, we typed 62 extant free-ranging wild gaur individuals for mitochondrial partial displacement loop (D-loop) and cytochrome b gene (Cyt b) from the Melghat Tiger Reserve (MTR). Two historical DNA samples originating from museums and two Tectona grandis bark fibers samples browsed by wild gaur were also used as a source of environmental DNA. Both D-loop and Cyt b loci show the occurrence of a single haplotype in the contemporary wild gaur population. While D-loop fragment sequencing of two historical museum samples reveals two unique haplotypes, virtually absent in the present wild gaur population of MTR. Amplifications of the similar haplotypes in gaur DNA samples obtained through chewed T. grandis bark fibers have proved the efficacy of eDNA. Bayesian Skyline Plot (BSP) analysis using extant and historical D-loop sequences illustrate population decline starting from upper Mesolithic. Also, the BSP graph indicates accelerated effective population size decline (Ne), a time period coinciding with the different phases of the ∼5000 years old Indus civilization. The plot shows an overall declining trend in the wild gaur population, a probable outcome of ever-shrinking habitat in the central Indian landscape caused by prehistoric, medieval and colonial hunting practices.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".