Multi-wavelength fluorometry for anaerobic digestion process monitoring
Bibliographic record
Abstract
Applicability of multi-wavelength fluorometry for anaerobic digestion process monitoring was investigated in a 3.5 L upflow anaerobic sludge bed (UASB) lab-scale reactor. Both off-line and on-line monitoring of key process parameters was tested. Off-line emission spectra were measured at an angle of 90 degrees to the excitation beam using a cuvette. On-line measurements were carried out using a fiber optic probe in the external recirculation line of the digester. Fluorescence spectra were correlated to available analytical measurements to obtain partial least square regression models. An independent set of measurements was used to validate the regression models. Model estimations showed reasonable agreement with analytical measurements with multiple determination coefficients (R2) between 0.6 and 0.95. Results showed that offline fluorescence measurements can be used for fast estimation of anaerobic digestor effluent quality. At the same time, the on-line implementation of multi-wavelength fluorescence measurements can be used for realtime process monitoring and, potentially, for on-line process control.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".