SENSORY AND PHYSIO‐CHEMICAL PROPERTIES OF MEMBRANE FILTERED APPLE JUICES<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT Shelf‐stable apple juices were prepared using two ceramic and four polymeric tubular membranes of varying pore sizes and evaluated using color matching and triangle tests. Juices from 9 kDa and 20 kDa membranes were different in color and aroma/flavor from the other membranes, the characteristics of which did not differ from each other. A full sensory profile was obtained for experimental juices produced using a 0.02 μm ceramic membrane and from commercial pasteurized apple juice. Experimental juices were prepared from fresh and stored apples with and without ascorbic acid. Twelve judges evaluated color; cooked/caramelized, appley, fruity and green aromas and seven flavor attributes (cooked/caramelized, appley, fruity, green, sweet, sour, astringence). Analysis of variance and principal component analysis revealed that membrane filtered juices lacked the cooked/caramelized aroma and had a green flavor compared with the commercial apple juice. Membrane filtered juices prepared from freshly harvested apples had less appley and fruity aroma and flavor, but were more sour and astringent than juices prepared from stored apples. Ascorbic acid treatment significantly reduced the yellow color and increased the astringence of juices.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".