ArticleScientific reports2021
Determination of quasi-primary odors by endpoint detection.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Overview of AI-Based Scent Creation.Sensors (Basel, Switzerland) · 2026Review
- Harnessing Explainable AI to Explore Structure-Activity Relationships in Artificial Olfaction.ACS applied materials & interfaces · 2025Article
- An Analytical Model of Sorption-Induced Static Mode Nanomechanical Sensing for Multicomponent Analytes.Analytical chemistry · 2025Article
- A Structure-Based Approach for Predicting Odor Similarity of Molecules via Docking Simulations with Human Olfactory Receptors.ACS omega · 2025Article
- OWSum: algorithmic odor prediction and insight into structure-odor relationships.Journal of cheminformatics · 2023Article
- Measurement of Volatile Fatty Acids in Silage through Odors with Nanomechanical Sensors.Biosensors · 2023Article
- Recent Advances in Nanomechanical Membrane-Type Surface Stress Sensors towards Artificial Olfaction.Biosensors · 2022Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is known that there are no primary odors that can represent any other odors with their combination. Here, we propose an alternative approach: "quasi" primary odors. This approach comprises the following condition and method: (1) within a collected dataset and (2) by the machine learning-based endpoint detection. The quasi-primary odors are selected from the odors included in a collected odor dataset according to the endpoint score. While it is limited within the given dataset, the combination of such quasi-primary odors with certain ratios can reproduce any other odor in the dataset. To visually demonstrate this approach, the three quasi-primary odors having top three high endpoint scores are assigned to the vertices of a chromaticity triangle with red, green, and blue. Then, the other odors in the dataset are projected onto the chromaticity triangle to have their unique colors. The number of quasi-primary odors is not limited to three but can be set to an arbitrary number. With this approach, one can first find "extreme" odors (i.e., quasi-primary odors) in a given odor dataset, and then, reproduce any other odor in the dataset or even synthesize a new arbitrary odor by combining such quasi-primary odors with certain ratios.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.