Investigating the effect of extrinsic cues on consumers' evaluation of red wine using a projective mapping task
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Consumers' perception (intrinsic sensory characteristics) of wine can be affected by extrinsic cues. This study aimed to determine the influence of extrinsic cues (price and label information/bottle) on consumers' sensory perception of red wine blends. A total of 202 participants (regular consumers of red wine), evaluated six red wine blends. Projective mapping (PM) and ultra‐flash profile (UFP) were used to characterize the wines in three separate sessions: blinded, presented with the bottle, and presented with their price. Participants separated the red wine blends based on sweet, fruity, bitter, and peppery attributes. RV coefficients indicated that the presentation of the bottle and label information affected the participants' results, and the PM sessions were not significantly correlated (RV = 0.500). The participants' results were affected by the brand name presented on the wine bottle. However, the blinded and price PM sessions were correlated (RV = 0.733). The consumers were able to evaluate the wines using the PM and UFP method. The extrinsic cues, except for the brand name, did not affect consumers' descriptions of the different wines. Practical Applications Projective mapping (PM) asks participants to express similarities and differences between samples, as well as position samples on a two‐dimensional plane. PM is usually paired with ultra‐flash profiling and allows researchers to identify the main attributes that account for differences among the samples. This study investigates the effect of extrinsic cues (bottle/label information and price) on consumers' evaluation of red wines blends. Brand names were found to affect consumers' evaluations. Understanding how consumers use label information and price when making their purchase decision is vital to both winemakers and for package design of wines.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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