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SELECTION OF AN ASTRINGENCY REFERENCE STANDARD FOR THE SENSORY EVALUATION OF BLACK TEA

2004· article· en· W2154777645 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Sensory Studies · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsAstringentTannic acidBlack teaTasteChemistryFood sciencePsychologyBitter tasteAlumOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT Astringent and bitter sensations are characteristic sensory qualities of black tea. Three different classes of potential astringent reference standards (two concentrations each of alum and tannic acid and three fruit juices) were evaluated in this study. The perceived astringency, bitterness and sourness of each were profiled using computerized time‐intensity and compared with the astringent intensity of a standardized brew of black tea. The differences in temporal profiles of potential reference standards across taste attributes were evident and intensity ratings were found to be dependent upon the stimulus and its concentration. Both concentrations of tannic acid were evaluated as the highest in perceived bitterness. For the juices, a strong sour taste was perceived in addition to astringency. It was concluded that the best reference standard for the astringency of black tea is a solution of 0.7 g/L alum as it is low in perceived bitterness and sourness.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0000.000

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 head0.259
GPT teacher head0.415
Teacher spread0.156 · 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