Matrix interference reduction for the analysis of carbohydrate in wastewater using H-point standard addition method
Bibliographic record
Abstract
Soluble microbial products, consisting of protein, carbohydrate and humics, are generally considered as the main membrane foulants during the performance of membrane bioreactors. Nitrate and nitrite have been proved to affect the determination of carbohydrate when anthrone-sulfuric acid photometric method is used. In this study, three chemical analytical methods based on photometric assay, including the standard curve method, conventional standard addition method and H-point standard addition method, were assessed for the quantification of carbohydrate in order to reduce the interference. Three methods were carried out for both artificial and real wastewater sample analysis. The results indicated a significant amount of matrix interference, which could be eliminated through the use of H-point standard addition. This study proposed the H-point standard addition method as a more accurate and convenient option for carbohydrate determination.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".