Monitoring the influence of wastewater effluent on a small drinking water system using EEM fluorescence spectroscopy coupled with a PARAFAC and PCA statistical approach
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
The potential use of a statistical approach for the investigation of complex dissolved organic matter (DOM) sources in surface water within a recycled water system monitored by excitation-emission matrix (EEM) fluorescence spectroscopy is shown. The work in this manuscript utilize information extracted from EEM spectroscopy to characterize DOM in collected surface water samples along with a wastewater treatment plant to drinking water treatment plant, discussing that humic-like and protein-like DOM sources predominate in the investigated water samples. Five different fluorescent components were resolved, describing several different types of DOM with different excitation and emission spectra that were distinct among the watershed sampling sites and indicating the influences of anthropogenic impacts. In addition, these novel fluorescence parameters have potential to improve resolution to direct more targeted water quality monitoring approaches.
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 | 0.001 | 0.001 |
| 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 it