MODELING OF SWEET, BITTER AND IRRITANT SENSATIONS AND THEIR INTERACTIONS ELICITED BY MODEL ICE WINES
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
ABSTRACT Interactions between taste and irritant sensations elicited by model ice wine solutions were investigated, including the use of U and Γ′ models for predicting the perceived intensity of these sensory interactions. Fifteen solutions of varying ethanol and sugar concentrations representative of commercial ice wine values were evaluated in two trials by a trained sensory panel ( n = 12) for perceived sweetness, bitterness and heat intensities. Sweetness perception of lower sugar‐concentration level in ice wine model solution was affected by ethanol concentration. The sweetness intensities of the sugar and ethanol mixtures are higher than the sweetness intensities of sugar solutions. The Γ′ index indicates a slight synergy between ethanol and sugar on sweetness perception. The bitterness intensities elicited by ethanol–sugar mixtures are lower than those elicited by unmixed ethanol solutions. The Γ′ index indicates inhibition of ethanol and sugar perception on bitterness perception. Suppression of heat sensation was found in model base wine solutions across sugar and ethanol concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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