Propiedades físicas y mecánicas de paneles a base de partículas de corteza externa de abeto blanco: Mezcla de paneles con partículas de madera versus fibra de madera
Bibliographic record
Abstract
El uso de la corteza externa de abeto blanco en la fabricación de canoas por las primeras naciones de Canadá es un ejemplo de su uso más antiguo. Esto confirma sus características hidrófugas, la cual puede ser explotada mediante su uso en la superficie del panel compuesto de 3 capas para protegerlo de filtraciones de humedad. Estos tableros fueron fabricados con partículas de corteza externa en las capas superficiales, y con partículas gruesas o fibras de madera en el corazón. Un experimento factorial en un diseño de bloque completo hizo posible realizar el diseño de experimento. Los dos grandes factores considerados, fueron el porcentaje de corteza en las capas superficiales con 3 niveles y el tipo de material usado en el corazón, con dos niveles respectivamente (partículas y fibras de madera). Cuatro réplicas fueron hechas para cada panel. Sólo los tableros con partículas gruesas de madera en el corazón pasaron todas las pruebas físicas satisfaciendo los requerimientos del interior de los tableros de partículas. Paneles con 45% de partículas de corteza en la superficie y 55% de partículas de madera en el corazón fueron seleccionados como los mejores, debido a su buena estabilidad dimensional. AbstractThe use of outer white birch bark in canoes is an example of its oldest use by the first nations in Canada. This use confirms the hydrophobic characteristics of this bark, which can be capitalized on by using it in the outer layers of three-layer mixed composite panels in order to protect them from water infiltration from their surface. These panels were made up of outer white birch bark particles in the surface layers with coarse wood particles or wood fibres in the core layer. A factorial experiment used in a complete block design permitted to carry a suitable statistical analysis of measured properties. The two main considered factors were respectively the bark percentages in the surface layers with three levels and the type of material used in the core with two levels. Four replicates were done for each panel. The panels with wood particles in the core layer gave physical and mechanical properties satisfying the indoor requirements for particleboards and those with wood fibres in the core layer passed the requirement of medium fibres density board. Panel with 45% bark particles in the surface and 55% wood particles in the core was selected as the best because of its good dimensional stability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".