Pulsed electric field assisted juice extraction
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.
Bibliographic record
Abstract
Purpose of the Review: Recently, there has been ren ew ed interest in the extraction of juice and functional ingredients from fruits and v egetables. Several consumer-related factors support the adoption of non -thermal technologies. This paper reviews application of pu lsed electric field (PEF) in juice extraction processes. It highlights novel designs of extractors that allow simultaneous applicati on of PEF and p ressure. Parameters that influence juice extracti on and juice quality issues are also discussed. Ma in findings: PEF can be used successfully to induce electroplasmolysis or ho mogenisation of tissues and intensify juice extraction fro m fruits and vegetable materials. The PEF must be applied strategically in order to optimise juice extraction. D irections for Futu re Research: Future studies on PEF-assisted juice extraction will involve applications to extract specific chemical c omponents alone with the juice, optimisation of the different PEF p arameters to obtain desired extraction kinetics and detailed ch emical evaluation of extracts to validate quality. There is currently limited or no commercially available equipment. Equipment manuf actur ers may be involved to design and fabricate easy-to-use PEF extractors. Ke ywords: Pu lsed electric field; juice extraction; elect roplasmolysis; juice quality; pressure; energy
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it