Evaluation of innovative water treatments at molecular level based on high resolution mass spectrometry and advanced statistical tools
Bibliographic record
Abstract
This work aims at integrating the last advances in high resolution mass spectrometry (HRMS) and statistical analysis to develop and optimize a smart methodology (workflow) for the assessment of the performance of innovative water treatments using different technological approaches based on advanced oxidation processes with UV-254nm: (i) UV/K2S2O8, where oxidation takes place mainly following the initial formation of sulfate radicals, (ii) UV/KHSO5, where oxidation begins with the formation of both sulfate and hydroxyl radicals and (iii) UV/H2O2, when only the formation of hydroxyl radicals takes place initially. Experiments were carried out using secondary effluent from a local wastewater treatment plant. The developed workflow allows the evaluation of the treatments in terms of overall oxidation through the careful study of Van Krevelen diagrams, where all information of the HRMS chromatograms is considered. The potential formation of transformation products with sulfur due to the sulfate radicals was also evaluated using statistical tools based on the accurate mass and the isotopic pattern. In a similar way, the potential addition of halogens was also assessed. Finally, the behavior of a large number of micropollutants with a wide range of physicochemical properties was studied using suspect screening strategies.
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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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".