Thermal Taster Subgroups and Orosensory Responsiveness Dataset
Notice bibliographique
Résumé
Thermal taste is a phenomenon whereby some individuals, known as thermal tasters (TT) experience taste sensations when their tongue is warmed or cooled. It was first reported in 2000 by Cruz and Green [1] and since then, most research has focused on comparing TT to thermal non-tasters (TnT; individuals who do not experience thermally-elicited sensations). As TT rate the intensity of taste stimuli higher than TnT, understanding the nature of this difference may help inform how individual differences in taste perception impact consumer liking and consumption of food and beverages. However, as the mechanism(s) underlying thermal tasting are yet to be fully elucidated, it is unclear if TT should be considered a homogeneous group or if subgroups exist. We created a dataset to help determine if the orosensory advantage is universal across all TT, or if it is mainly attributable to one or more subgroups of TT. To this end, the thermal taste screening data of 297 TT from 12 previous recruitment drives (‘cohorts’) was combined. This created the largest dataset of TT reported to date in a single study, allowing for an in-depth analysis of the differences between TT. After training on appropriate scale use, participants were familiarized with common taste and chemesthetic stimuli (sweet, sour, salty, bitter, umami, astringent and metallic). Using a sip-and-spit protocol, participants rinsed with the stimuli and rated the maximum intensity each stimulus elicited on a generalized Visual Analogue Scale (gVAS) or a generalized Labeled Magnitude Scale (gLMS). To account for minor methodological differences between the cohorts, ratings from each cohort were first converted to z-scores before being combined into the overall dataset. Next, participants underwent a series of 12 trials that assessed response to a thermal elicitation device during which each combination of two temperature regimes (warming and cooling) and three lingual sites (tongue tip, 1 cm to left, 1 cm to the right) were examined in duplicate. Participants were asked to rate the maximum intensity of any sensations experienced during each trial. TT were classified into subgroups based on the type of thermally-elicited taste reported (typically sweet, sour, salty, bitter, metallic), the temperature regime during which the sensation was elicited (warming or cooling) and the location on the tongue tested at which the sensation was experienced. Figures are provided that show the mean intensity ratings of aqueous solutions of chemical stimuli and corresponding standard errors for each of the TT subgroups. In addition, the TT Subgroup Naming Conventions provided should allow for a consistent and clear use of terminology across future thermal taste research. Readers are referred to Homogeneity of thermal tasters and implications for mechanisms and classification [2] for a full discussion of how these findings inform our understanding of the mechanism(s) underlying thermal taste and the practical implications of methodological differences in determining thermal taste status.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».