Effect of processing treatments on the characteristics of juices and still ciders from Ontario‐grown apples
Bibliographic record
Abstract
Abstract Recent interest in the commercial production of cider in Ontario, Canada revealed a lack of information on cider prepared from apples grown in North America. A study was conducted using locally grown culinary and dessert varieties of apples, since there is a lack of true cider varieties grown in Ontario. Four processing methods (treatments) were evaluated with respect to their effect on juice and cider characteristics; the chemical and microbiological characteristics of the juices and still ciders are reported. Sulphite addition to the juice at the time of juice extraction had no effect on the characteristics evaluated. Storage of fruits at 13 °C until they showed signs of shrivelling or senescence decreased juice yield and affected titratable acidity and pH levels of juices and ciders. Freezing fresh apples and thawing prior to processing produced juices that did not undergo keeving and had higher mould and yeast populations; methanol was present in juices and ciders from thawed apples. The significant effects of storage and freezing on apple juice characteristics should be taken into account when considering a delay in the processing of apples for cider production. © 2003 Society of Chemical Industry
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".