Characterization of The Physical Properties of Palm Kernel Cake
Bibliographic record
Abstract
A systematic sieving method (1 kg sample; 50 Hz; 0° inclination; 20 min) was used to obtain particle size distribution of palm kernel cake containing seven different particle sizes (4.83, 2.68, 1.50, 0.80, 0.51, 0.32, and 0.11 mm). Regardless of particle size, palm kernel cake was found to be of different shapes qualitatively with optical microscopy and quantitatively (variation in mean length, mean volume, and volume-surface mean diameters), non-porous (Brunauer-Emmett-Teller specific surface area <1 m2/g), and to contain an uneven rough surface, as shown in scanning electron microscopy. Palm kernel cake of 0.32 mm and less were aggregates with uneven rough surface, and those of 0.51 mm and more were agglomerates with interstices formed from particle agglomeration. These characteristics affected the bulk density of palm kernel cake that decreased with decreasing particle sizes due to lower packing density and higher void. The physical properties affected the hydration properties. This information is useful for the solid-state fermentation of palm kernel cake.
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How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".