Compression and springback properties of hardwood and softwood pellets
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
A multiple linear regression analysis was carried out to predict the length of pellets under compression in the die based on moisture, temperature, pressure, hold time, and their interaction terms. Excellent correlations were obtained in the dependency of the considered parameters on length of compressed material inside the die. Springback characteristics based on axial changes after the compaction process were analyzed. The expansion for hardwood pellets (16.28%) was found to be lowest at particle size 0.150 to 0.300 mm with 8% moisture (w.b), 60 °C, 139.3 MPa pressure, and a hold time of 15S. The expansion for softwood pellets (20.56%) was lowest with particle size 0.300 to 0.425 mm, at 8% moisture (w.b), 70 °C, 159.2 MPa, and a hold time of 30S.
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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 | 0.000 |
| 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) | 0.000 | 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 it