Evaluation of Al-Thagher Wastewater Treatment Plant
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
This study aims to evaluate the performance of the sewage treatment plant in Al-Thagher city, in the north of Basrah governorate, the southern part of Iraq. The plant’s performance was estimated based on an analysis of influent and effluent wastewater quality data that represented the monthly averages from Feb. 2017 to Dec. 2018. The results show that the values of temperature (T), pH, ammonia (NH3–N), chemical oxygen demand (COD) and biological oxygen demand (BOD) in all collected samples from the effluent of the plant met the Iraqi water quality standard (IWQS), whereas the values of electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), sulfate (SO4–2), chloride (Cl–1) and phosphate (PO4–P) met the Iraqi water quality standard (IWQS) in some months and did not meet the standard in other months. The average removal efficiencies were in the following order: COD (77.12%) > BOD (77.03%) > TSS (62.26%) > NH3–N (59.99%) > PO4–P (12.42%) > Cl–1 (1.97%). The removal percentages for the remaining parameters had negative values. The Canadian Council of Ministers of the Environment water quality index (CCME WQI) value of the treated water was 51.80 and classified as “marginal.” The coefficients of determination between each parameter in influent or effluent were calculated. Finally, linear regression equations between these parameters were formulated so that the value of one parameter could be used to predict the value of a different parameter.
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 | 0.001 | 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) | 0.007 | 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