Extraction of wax‐like materials from cereals
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
Abstract In this study, a comparison of the wax extraction process from rice, sorghum, and wheat using liquid nitrogen was done with respect to the traditional solvent extraction method using n ‐hexane. For this purpose, these cereals were immersed in liquid nitrogen (1–4 cycles with different time intervals and different rest times between cycles). The results showed that waxes could be extracted by liquid nitrogen, but with a lower yield. When compared to the n ‐hexane extraction method, the extracted amounts of waxes with liquid nitrogen were 5, 7.5, and 9.3 times lower, but the extraction times were 2.3, 5.5, and 11.25 times shorter for wheat, rice, and sorghum, respectively. No residue was left in wax‐like materials extracted with liquid nitrogen. While SEM depicted that the outer layer of waxes on the grains could be extracted by liquid nitrogen, GC‐MS and GC‐FID showed that the extracted waxes had similar compositions in both cycle extraction methods. These results could point out a novel environmentally‐friendly method to extract waxes from cereals that could be useful for certain applications.
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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 | 0.001 |
| 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 it