SELECTION OF AN ASTRINGENCY REFERENCE STANDARD FOR THE SENSORY EVALUATION OF BLACK TEA
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".