Bibliographic record
Abstract
Abstract Ginger paste was prepared from fresh ginger by addition of 8% common salt and citric acid. The paste was thermally processed and packed in glass, polyethyleneterephthalate or high-density-polyethylene containers and stored at 5 ± 1 and 25 ± 1 °C for 120 days. The rheological characteristics of the paste were studied by using a computer controlled rotational viscometer over the temperature range of 20–80 °C. Samples were subjected to a programmed shear rate, increasing linearly from 0 to 200 s−1 in 3 min, followed by a steady shear at 200 s−1 for 3 min and finally decreasing linearly from 200 to 0 s−1 in 3 min. Ginger paste exhibited pseudoplasticity with yield stress and flow adequately described by the Herschel–Bulkley model. The yield stress decreased exponentially with process temperature and ranged between 3.86 and 27.82 Pa. The flow behaviour index (n) varied between 0.66 and 0.82 over the temperature range. Both consistency index and apparent viscosity decreased with increase in temperature and the process activation energies were found to be in the range of 16.7 to 21.9 kJ mol−1. The effect of temperature was significant (P < 0.05) on the Hunter colour combination value of the paste during storage; however it was not affected by type of packaging material (P > 0.05). It is recommended that ginger paste is stored at 5 ± 1 °C in polyethyleneterephthalate or glass containers.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".