Model-based Analysis of Nitrogen Dynamics in the Tigris River in Baghdad City
Bibliographic record
Abstract
Developing a solid understanding of the nitrogen dynamics across the Tigris River is critical to evaluate the environmental degradation of the increased N fluxes. Nitrite, nitrate, and total oxidized N (nitrite+nitrate) were monitored from April 2018 to August 2019. Plug flow reactors and continuously stirred tank reactors in series models were implemented to explore N behavior in the river system. The results indicated that the total oxidized N decreased over the first half of the study period, then was followed by a high rate of nitrate production. These findings are also supported by changes of the river flow rates, dissolved oxygen, pH, and chemical oxygen demand. The models have the capacity to simulate N dynamics, with varied prediction errors. Root mean squared errors between measured and predicted nitrite, nitrate, and total oxidized N concentrations were 0.118, 2.595, and 2.560 g m-3, respectively, for the PFR model, while these values were 0.05, 0.175 g m-3, and 0.176 g m-3, respectively, for the CSTRS model. The correlation coefficients were 0.012, 0.925, and 0.922 for nitrite, nitrate, and total oxidized N, respectively, when the PFR model was applied. These values were 0.92, 0.99, and 0.99, respectively, after the application of the CSTRS model. Obtained results revealed that the modeling approach can provide a useful framework to improve understanding of N dynamics, which helps to develop mitigation strategies for sustaining water quality in the Tigris River.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".