Bibliographic record
Abstract
This paper assesses the water quality index of 11 streams (rivers) and the receiving UM- AL NAAJ marshland at Misan governorate and how the water quality is improved when entered the marshland. The assessment employ the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) which incorporates three elements: Scope (F 1)- the number of water quality parameters not meeting water quality objectives; Frequency (F 2)- the number of times the objectives are not met; and Amplitude (F 3)- the extent to which the objectives are not met. The index produces a number between 0 (worst) to 100 (best) to reflect the water quality. Iraqi guidelines for drinking water and the site-specific measured values of 5 variables are used in the index calculation.Variables included in the index calculation were, water temperature, dissolved oxygen, total dissolved solids, pH, turbidity. The CCME WQI analysis show that the average water quality of the 11 streams, feeding Um- Alnaaj marshland is rated as fair based on 2010 data, meaning that the conditions of the streams were sometimes depart from natural or desirable levels while the quality of water inside the marsh was ranging from good to excellent.
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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 | 0.000 |
| Scholarly communication | 0.001 | 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".