THE PHYSICO-CHEMICAL ENVIRONMENT AND AQUATIC BIODIVERSITY OF HEAD MARALA WETLAND DURING 2000-2001
Bibliographic record
Abstract
An ecological study on Head Marala Wetland was undertaken.The study will help in providing sound basis for the future conservation activities and its management, on sounder footing.The Marala wetlands in Bajwat area included river Jammu Tawi, river Chanab and river Manawar Tawi were studied for a period of one year, i.e. from October, 2000 to September, 2001.In this study, 36 Phytoplanktons belonging to six families were observed.The other aquatic fauna observed included 14 species of fish, 2 turtles, one leech, one prawn, one shrimp and one bullfrog.The results showed that physico-chemical parameters had an impact on the biodiversity and population size of the aquatic fauna at Head Marala wetlands.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".