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Record W4406063855 · doi:10.1016/j.foodres.2025.115670

The espresso protocol as a tool for sensory quality evaluation

2025· article· en· W4406063855 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFood Research International · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsnot available
Fundersnot available
KeywordsProtocol (science)Sensory systemQuality (philosophy)Computer scienceComputational biologyBiologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

• Initial and overall quality scores were comparable, except for those in the defective sample. • Check-all-that-apply method was utilized to characterize sensory attributes of espresso. • The US/Canada and Australia/New Zealand coffee experts evaluated espresso similarly. • Blind duplicates were evaluated similarly, reflecting consistent measure of the protocol. • The defect was perceived during flavor evaluation only. Espresso is prepared differently from filter coffee as pressure extracts flavor components from ground coffee. Nowadays it is enjoyed by many as it is or in espresso-based drinks. The Espresso Protocol (TEP) is a new method for assessing the quality of espressos by utilizing sensory evaluation techniques, such as the just-about-right (JAR) scale and the check-all-that-apply (CATA). This study aimed to evaluate the discriminability of TEP. Coffee experts from the US/Canada (n = 32) and Australia/New Zealand (n = 31) participated in the study. Twelve coffees were shipped for evaluation using espresso machines in their respective homes. As a result of the response analysis using the frequency of CATA to identify the participants’ coffee culture differences, no significant cultural differences were identified in the two groups, the US/Canada and Australia/New Zealand. CATA results enabled discrimination among samples and were able to indicate characteristics associated with high quality coffee and able to identify ‘defect’ in samples. Defect due to container contamination was perceived from flavor evaluation only. There was no significant difference between the initial quality score and overall quality scores evaluated at this tool’s beginning and end, except for the defective coffee sample. Between the percentages of participants who were willing to use the bean for espresso extraction and overall quality scores, there was a high correlation. Penalty analysis coupling overall quality score and just-about-right evaluations of each category indicated their influence on quality perception. Furthermore, no significant differences between blind duplicate coffee samples confirmed consistent measurement of this tool. TEP can be used to evaluate the quality of coffee beans for espresso by coffee experts.

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)0.007
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.376
GPT teacher head0.583
Teacher spread0.207 · 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