Investigating How the Disclosure of Production Methods Influences Consumers’ Sensory Perceptions of Sparkling 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
The primary objective was to identify how the disclosure of production methods, including sustainable practices, would impact consumers’ sensory perceptions. The secondary objective was to identify the attributes consumers use to describe Nova Scotia (NS) sparkling wines. The first trial used projective mapping (PM) and ultra-flash profiling (UFP) to describe eight sparkling wines (n = 77). In the second trial, a check-all-that-apply (CATA) questionnaire and 9-point hedonic scales were used (n = 101). Three sparkling wines, from the previous trial, were evaluated blinded and with a production claim. The first trial found that consumers separated the wines based on their fruit- or earth-like attributes. In the CATA trial, desirable attributes, such as sweet and smooth, were used more frequently to describe the wines with sustainable production methods. No significant differences were found in the overall liking scores after the disclosure of the production methods (α = 0.05). These findings indicate that disclosure of production methods did not impact participants’ sensory perceptions of sparkling wine. In addition, an evaluation among different generations should be considered, as millennials have been found to hold sustainable practices to greater value.
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 | 0.001 |
| 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 | 0.001 |
| 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