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Record W4200179880 · doi:10.3390/beverages7040080

Consumer Perception of Milk and Plant-Based Alternatives Added to Coffee

2021· article· en· W4200179880 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBeverages · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsAcadia University
Fundersnot available
KeywordsSweetnessFood scienceSoy milkBusinessFlavorBiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.285
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it