Environmental impacts on seasonal fish diversity in Jamuna River, Bangladesh
Bibliographic record
Abstract
Jamuna River is one of the vital rivers in Bangladesh for its rich aquatic biodiversity. A total of 52 fish species were recorded during the study period, belonging to 9 orders, 20 families, from the three selected locations of the river. Fish populations are the highest during the dry winter season and the lowest during the monsoon season. The mean values of Shannon-Weaver diversity, Margalef's richness, and Pielou's evenness indices recorded as 3.29± 0.02, 0.58±0.01, and 7.00±0.10, respectively, varied from season to season. Nonmetric MDS and Canonical Correspondence analysis were used to evaluate the effect of environmental factors on the structure of the fish assemblage. The Nonmetric Multidimensional Scaling (nMDS) had attained in two groups in the cluster analysis, one of which showed the association of the fish samples between the summer and winter seasons, and the other included the species from the monsoon season among the sampling sites. The fish species responsible for the fluctuation in seasonal abundance up to a cumulative dissimilarity of 21.85%, and four species were responsible for this dissimilarity. Canonical correspondence analysis on the fish community was used to demonstrate the fascinating functions of alkalinity, total dissolved solids, electrical conductivity, and dissolved oxygen in Jamuna River.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".