Optimising microwave vacuum puffing for blue honeysuckle snacks
Bibliographic record
Abstract
Abstract Fresh blue honeysuckle fruit slices were puffed in a microwave vacuum dryer up to a final moisture content about 5% (w.b.). The effect of initial moisture content (IMC) (25–45%), vacuum pressure (VP) (70–90 kPa) and microwave intensity (MI) (10–30 W g−1) on quality attributes, in terms of expansion ratio (ER), hardness (HD), crispness (CR) and colour of the products, were analysed by response surface methodology. Besides the effect of MI on chroma (CH), the high IMC and low VP had a significantly positive impact on the quality attributes of blue honeysuckle snacks. The optimum product qualities, which were ER (1.62 times), HD (5836.31 g), CR (4.48), and CH (28.7) were obtained at an IMC of 38.42%, VP of 82.02 kPa, and MI of 22.42 W g−1. The microwave vacuum method has obvious advantages when puffing the blue honeysuckle snacks.
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.
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 | 0.000 |
| 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".