Measurement of Odour Concentration of Immissions using a New Field Olfactometer and Markers' Chemical Analysis
Bibliographic record
Abstract
A novel field olfactometer, Scentroid SM110 (IDES Canada Inc., 2012), based on a new technology, has been tested in comparison with another portable olfactometer, Nasal Ranger (St. Croix Sensory Inc., 2003). Responses of both devices during a measurement campaign were compared with odour predicted values by a dispersion model and with chemical data of emission marker’s analysis.The measurement test was performed in an anaerobic digestion plant located near Vicenza (Italy) and one typical odour source was a biofilter with an emission of 350 ouE/m3. The objective of this study is to compare different techniques (field olfactometry, marker’s analysis, dispersion model) for assessing the concentration of odour in ambient air. The analysis of results shows a clear and measurable influence of background odour in ambient air, resulting in higher odour levels when measured using field olfactometry than is predicted using chemical analysis or dispersion modeling. Furthermore, a good agreement was found between chemical data and predicted values from CALPUFF dispersion model.
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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) | 0.000 | 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 | 0.001 | 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 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".