Electrohydrodynamic drying: The opportunity for sustainable development
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
This review presents electrohydrodynamic (EHD) drying as a new advanced technology to increase awareness of professionals on the great opportunity to contribute to the sustainable future of humanity. This emerging technology, which exploits the phenomenon of ionic wind for direct extraction of liquid water from wet materials, has been described considering product quality, energy consumption, efficiency, and environmental protection from the emission of greenhouse gases. The economic analysis of this new technology showed that EHD drying has great potential to reduce food losses in production and distribution chains, as well as minimize waste from restaurants and households. The sustainability of EHD drying, based on capital and operating costs, energy and exergy efficiency, and social implications, is illustrated, using the example of EHD-assisted convective drying.
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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 | 0.001 |
| 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