Effects of vegetative barriers for channelization of Shiwalik torrent at Sabhawala in Doon Valley (India).
Bibliographic record
Abstract
The composition and abundance of benthic animals are commonly used as bio-indicators to determine the impact of pollution on physico-chemical integrity of surface waters and changing pattern of biotic characteristics of lentic and lotic system. The benthos serves as a link between primary producers, decomposers and higher trophic level. Song river is a spring fed hill stream originated from different small rivulets of lesser Himalayan mountainous ranges at Garhwal region of Uttarakhand. The study was carried out from 2006-2008, the water samples were collected from three different sites in a stretch of about ten kilometres from Song river. All taxa were identified to species/genus level with the help of identification keys. The 5 faunal groups and 19 genera were observed at three different stations in the Song river. At all three sites, Tubifex was the dominant genera among Oligochaeta. Among polychaeta, Namalycastic indica, Napthys polybranchia, Napthys oligobrunchia species were reported at all above three different sites of Song river. Biotic indices indicated moderate pollution in the water quality of upstream and down stream water. The CCME (Canadian Council of Minister of Environment) water quality index (2001) showed marginal range of pollution in the river. The abundance of pollution tolerant organisms indicated the downstream site is receiving nutrient-rich urban runoff containing little or no toxins substances.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".