Taste sensitivity and taste preference measures are correlated in young healthy adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Taste is fundamentally important for food selection. While measures of taste sensitivity and taste preference have been refined over several decades, it remains largely unknown how these measures relate to each other and to food preferences. The objectives of this study were to examine, in healthy adults (age 24.6 ± 0.6 years, n = 49), 1) correlations among measures of taste sensitivity, including detection threshold (DT) and suprathreshold sensitivity (ST), and taste preference (PR) within sweet, salt, sour, umami, and fat tastes, 2) the underlying associations among DT, ST and PR measurements using principal component analysis, and 3) associations between measured PR (all tastes) and bitter ST with self-reported food preferences. As expected, DTs and STs were negatively correlated within each taste modality. Salt, sweet, and umami DTs and STs were positively and negatively correlated with PRs, respectively. No correlations were observed between sour and fat DTs, STs and PRs. Two principal components accounted for 41.9% of the variance and produced three clear clusters, where each cluster generally consisted of DTs, STs or PRs from each taste modality. Sweet PR and fat ST deviated from the clusters and may therefore be driven by different factors. No associations were observed between measured PR and ST with self-reported food preferences. Overall, this study provides evidence that higher sensitivities only to salt, sweet, or umami taste are associated with a decrease in the preference for these tastes. These findings demonstrate the importance of investigating taste sensitivity together with taste preference to gain a more complete understanding of the determinants of food selection. (Support was provided by the Ontario Ministry of Agriculture, Food, and Rural Affairs)
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it