Consumer Perception of Milk and Plant-Based Alternatives Added to Coffee
Bibliographic record
Abstract
Consumers have begun to use plant-based alternatives (PBAs) in their coffee instead of dairy products. PBAs can include soy milk, rice milk, coconut milk, almond milk, oat milk, and hemp milk. The objective of this study was to investigate consumer acceptability and sensory perception of coffee with added dairy milk and added oat, soy, and almond PBAs. Consumers (n = 116) that frequently add milk to their coffee (n= 58) and consumers that usually use PBAs (n = 58) were recruited to participate in the study. They evaluated four different coffee samples with the addition of dairy milk as well as soy, almond, and oat PBAs. Overall, the consumers liking increased when they perceived sweetness in their coffee. The plant consumers (usually added PBAs to their coffee) liked the milk addition significantly less than the dairy consumers (usually added dairy to their coffee). In addition, the plant consumers were able to differentiate between the almond and soy PBAs, while the dairy consumers grouped them together. More studies need to be completed to investigate a wider range of PBAs, dairy products, and varieties of coffee.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".