Static and dynamic methods to determine adsorption isotherms of hemp seed (<i>Cannabis sativa</i> L.) with different percentages of dockage
Bibliographic record
Abstract
Adsorption and desorption isotherms of hemp seeds with 0%, 5%, 10%, 15%, and 20% of dockage were determined using the salt solution static (SSS) method. The wet hemp seeds with 0% dockage were also dried at 30℃ with 50% RH, 35℃ with 30% and 50% RH, and 40℃ with 30% and 50% RH inside a thin-layer dryer (thin-layer dynamic method). The hemp seeds with different percentages of dockage showed hysteresis, and this hysteresis became more obvious with the decrease of temperature. At the same condition, the equilibrium moisture content of hemp seeds with 0% dockage was approximately 0.5 percent points lower than that of the hemp seeds with dockage. The best equation to fit the equilibrium moisture content data under constant temperature and RH was the modified GAB equation for both adsorption and desorption isotherms. The constant rate period of drying was observed for <0.75 hr when drying air RH was 30% or when drying air temperature was 40℃. The Henderson and Pabis model was the best model to fit the thin-layer drying data. The equilibrium moisture contents measured by the SSS method were lower than those measured by the thin-layer dynamic method when temperature was ≤35℃.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".