PHYSICAL AND MECHANICAL PROPERTIES OF PANEL BASED ON OUTER BARK PARTICLES OF WHITE BIRCH: MIXED PANELS WITH WOOD PARTICLES VERSUS WOOD FIBRES PROPIEDADES FÍSICAS Y MECÁNICAS DE PANELES A BASE DE PARTÍCULAS DE CORTEZA EXTERNA DE ABETO BLANCO: MEZCLA DE PANELES CON PARTÍCULAS DE MADERA VERSUS
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
The use of outer white birch bark in canoes is an example of its oldest use by the fi rst nations in Canada. This use confi rms 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 infi ltration from their surface. These panels were made up of outer white birch bark particles in the surface layers with coarse wood particles or wood fi bres 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 fi bres in the core layer passed the requirement of medium fi bres 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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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 it