Study of the Swelling of a Composite Based on Argan Nut, Urea-Formaldehyde and Water as a Non-Polluting Solvent
Bibliographic record
Abstract
In the center and southwest of Morocco, there is an endemic tree «Argania Spinosa» known as the ironwood. The miraculous product of this millenary tree is argan oil. Known for its therapeutic and cosmetic properties. Only 20% of the fruit of the argan tree is intended for the manufacture of argan oil while the shell, which represents 80%, remains an unexploited resource. This hull, which is sold by farmers at low prices, is used as fuel for baths and Moorish bakeries. In order to value the shells; first, we sort, grind and sieve them. Second, we bind the particles into adhesive. Three biomaterials are based on three particle sizes of shell grains. The designed particles are bound with an adhesive powder that is produced from a pre-catalyzed urea-formaldehyde resin. Moreover, the water used is a non-polluting solvent. The biomaterials and two samples of Red and Beech Wood were immersed in water for 15 days, with mass measurements that were done on a daily basis. It was concluded that the swelling coefficient of the large distribution of biomaterial is smaller than the small distribution of biomaterial. However, Red and Beech Wood have the highest coefficient.
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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".