Bibliographic record
Abstract
Cross-laminated timber (CLT), an engineered wood product categorized as “mass timber,” is gaining popularity in residential and non-residential applications. The prospect of building larger timber structures creates structural challenges, amongst them being that lateral forces created by high winds and strong earthquakes are higher and create higher demands of “hold-downs.” These demands are multiple: high strength to resist loads, high stiffness to minimize deflections during wind events, as well as deformation compatibility to facilitate the desired rocking-motion of the shear walls during an earthquake. Herein, recent research on several innovative hold-down solutions will be provided: internal-perforated-steel-plates fastened with self-drilling dowels; hyperelastic rubber pads with steel rods; and solutions with self-tapping screws. All systems are capacity-protected in the non-dissipative components: strength, stiffness, and ductility is governed by the energy-dissipative shear wall components. The results from component-level and full-scale CLT shear wall tests are presented. The findings provide design guidance to practicing engineers and will inform future revisions of the Canadian Standard for Engineering Design in Wood.
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.
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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".