Heterotrophic Bacterial Population in Water, Sediment and Fish Tissues Collected From Koka Reservoir and Awash River, Ethiopia
Bibliographic record
Abstract
The quantitative estimation of total heterotrophic bacteria in the water, sediment and body tissues is helpful in predicting the quality of the fish as well as the status of the water body. The bacterial population in the water of Koka Reservoir and the Awash River, studied monthly for a period of one year, showed variation from 0.0.2×10 4 cfu/ml to 2.6×10 4 cfu/ml. Whereas, in the sediment the highest population density was 2.6 cfu/g and the lowest was 0.98×10 4 cfu /g. The highest population density in the reservoir was recorded in the sediment in January, while in the water was in August. The heterotrophic bacteria population in the river water and sediment was lower than the reservoir. During the non rainy season (February and March) the sediment bacteria increased with increase in water temperature and reduced rate of water level. The bacteria in the river water greatly reduced during February even though a regular pattern was not evident throughout the study period. The total bacterial population in different tissues of Cyprinus carpio and Oreochromis niloticus showed maximum population in intestine, followed by gill, skin, kidney and liver
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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 | 0.000 |
| 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 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".