Managing Odour Sample Degradation through On-Site Olfactometery and Proper Sample Transportation and Storage
Bibliographic record
Abstract
Degradation is inherent part of odour sampling and olfactometery analysis. There are many techniques that can be deployed in order to minimize sample degradation, such as nitrogen-based pre-dilution and sealed transportation vessels. Despite the best efforts to keep the volatilization at bay - sample degradation has forced European and American standards to implement a thirty (30) hour expiration on all odour samples. German standard VDI3880, and possible the soon to be revised EN13725 standard, limit sample storage to 6 hours unless it can be shown that the sample degradation is within acceptable limit. On-site olfactometers such the Scentroid SM100, can be used, and are widely used in Canada, as part of the quality assurance program by measuring samples immediately after acquisition and immediately prior to analysis by the laboratory to ensure odour degradation is within these defined limits. However, observations have shown samples can degrade by an order of ten magnitudes in a span of less than 24 hours. This study provides data on sample degradation from a variety of sources over a span of 24 hours. Samples will be stored in Nalophan, Tedlar®, and the newly introduced PTFE bags. Data has shown that the much higher density of PTFE provides slower sample degradation than Tedlar® or Nalophan. This is especially true of samples with high humidity, Ammonia, or H2S. To properly simulate shipping conditions a portion of the study focuses on samples that are subjected to lower pressure and temperature similar to those found in standard cargo planes. These samples are compared to those which have been stored at standard conditions (room temperature at 1 atmosphere). Further study has been made on degradation of sample with highly volatile compounds such as ozone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".