Human-like smelling of a rose scent using an olfactory receptor nanodisc-based bioelectronic nose
Bibliographic record
Abstract
We report a strategy for the human-like smelling of a rose scent utilizing olfactory receptor nanodisc (ND)-based bioelectronic nose devices. In this strategy, a floating electrode (FE)-based carbon nanotube (CNT) field effect transistor (FET) was functionalized with human olfactory receptor 1A2 (hOR1A2)-embedded NDs (hOR1A2NDs). The hOR1A2NDs responded to rose scent molecules specifically, which were monitored electrically using the underlying CNT-FET. This strategy allowed us to quantitatively assess the contents of geraniol and citronellol, the main components of a rose scent, as low as 1 fM and 10 fM, respectively. In addition, it enabled us to selectively discriminate a specific rose odorant from other odorants. Significantly, we also demonstrated that the responses of hOR1A2NDs to a rose scent could be strongly enhanced by enhancer materials like a human nose. Furthermore, the method provided a means to quantitatively evaluate rose scent components in real samples such as rose oil. Since our method allows one to quantitatively evaluate general rose scent ingredients just like a human nose, it could be a powerful strategy for versatile basic research and various applications such as fragrance development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".