Product development approach to introducing a new wine style and grape varietal: <i>Marquette</i>
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
Interspecies hybrid grape varieties make up a substantial portion of grape production around the world. They can provide superior disease resistance and climate adaptation along with interesting, distinct flavour profiles. Marquette, a recently introduced cold-hardy, hybrid varietal has limited research to date on sensory profiles and consumer perception. This study sought to define consumer acceptance and sensory profiles of Marquette so that viticultural and oenological practices can be targeted to make consumer-friendly wines. Red wine consumers (n = 113) evaluated commercial Marquette and other red wines (hybrid and non-hybrid) and trained assessors profiled wines using a rapid technique. Results were used to define sensory drivers of liking and to characterize consumer segments through correlation to sociodemographic factors, including wine knowledge. Overall, Marquette wines with a fruit-forward or spicy + savoury flavour were preferred by novice consumers (20% and 27% of respondents, respectively). For more knowledgeable and wine-interested consumers (53% of respondents), the recommended profile is dark fruit, herbaceous flavour and full-body. These findings and approaches can be used as a roadmap for winemakers looking to produce and market Marquette. Additionally, this approach can be applied to understand the sensory profiles and consumer perception of other novel or non-traditional wines.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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