Studies on Spatial and Seasonal Variation of Water Quality and Fish Species Diversity in the Man stream, Shivalik, Himalayas, India Using the ArcGIS Mapping System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present study assesses the water quality of the Man stream, a significant tributary of the Beas River in Shivalik Himalayas, Himachal Pradesh, by analyzing environmental variables, Water Quality Index (WQI) and fish species distribution using the Geographical Information System (GIS). Water samples were collected from two sites (upstream and downstream), over a year and various physiochemical parameters were analyzed. The study utilized the Canadian Council of Ministers of Environment - Water Quality Index (CCME-WQI) to evaluate water quality, depicting "fair" to "marginal" water quality status. Pearson’s correlation coefficient was used to assess the correlation between physiochemical parameters. A total of 23 fish species belonging to 6 orders and 9 families was reported, with Cypriniformes being the dominant order. Diversity indices revealed seasonal variations in fish communities, with the highest dominance index during monsoon and the Simpson and Shannon indices lowest during monsoon and nearly the same during pre-monsoon and post-monsoon with insignificant fluctuations. This comprehensive assessment provides valuable insights for fishery management and sustainable development in the region.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it