Drying Characteristics of Purslane (<i>Portulaca oleraceae</i>L.)
Bibliographic record
Abstract
Thin layer drying rates of purslane were determined experimentally as a function of temperature with air velocity kept constant at 1.1 m/s and relative humidity below 5%. Thin layer drying data were obtained for purslane at four drying air temperatures (35, 70, 95, and 120°C). Five thin layer-drying models (Henderson and Pabis, exponential, Page, two-term exponential, and Thompson models) were fitted to the drying data. The color of purslane was determined after drying using a spectro-colorimeter (Hunter Lab) in terms of Hunter L, a, and b values. The Page model was found to be most suitable in describing the drying characteristics of purslane. New parameters developed for the model resulted in a good fit at different temperatures. Color measurement indicated that greenness decreased with an increase in drying air temperature. Typical drying times were 88.41, 138.53, 416.38, and 1371.85 min at 120, 95, 70, and 35°C, respectively.
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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".