A New State of the Art Stationary Dynamic Dilution Olfactometer
Bibliographic record
Abstract
Public awareness towards environmental odours has increased with higher living standards. Still, nowadays, no instrument can yet replace the human’s specific perception of odours because of the complexity of the relationship and interaction between the odour constituting gases. Olfactometry, which is the science of measuring odours, remains the only statistical method to characterize odours and their effects on human perception. This relatively recent science has evolved since the early 1970’s and is now regulated by international guidelines available in Europe (CEN 13725, 2003; VDI 3882, 2003) and North America (ASTM 679, 2011). These guidelines recommend the use of a specific instrument to characterise odours using a jury of “noses”. This instrument is called an olfactometer. This paper will present a state-of-the-art stationary dynamic dilution olfactometer designed by Consumaj. This dynamic olfactometer meets the European and North American standards in olfactometry analysis. This paper will emphasize the process of design and development involved in the concept of this dynamic olfactometer in order to meet the different international standards and to provide accurate and precise odour measurements. This stationary olfactometer, named Onose-8®, is presently in operation at Consumaj laboratories, in StHyacinthe, Canada. This olfactometer is designed to accommodate up to 16 assessors simultaneously, which meets the VDI 3882 (2003) standards. This particularity is made possible because of its nonagon (9-sided) shape providing ergonomic features for more comfort, space and ease of work to the assessors. The dilution of odorant samples with fresh air is performed using mass flow controllers that can also be automatically verified and calibrated using a protocol provided with the interface software that controls the olfactometer.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".