Dowel-laminated puncheons: a high-performance, low-waste mass timber assembly
Bibliographic record
Abstract
Converting a log to rectilinear timber adds constructional convenience, but also incurs material waste and consequent loss of structural capacity. Puncheons were a pre-industrial timber product: a log flattened on three faces and left “live” on the fourth. They were typically employed in log structures in a one-way mass-timber floor slab, not unlike dowel laminated timber (DLT). In 2022 an instructor at Dalhousie University (Jannasch), his co-authoring grad students, and ten teammates compared the values gained and lost in puncheons vs. conventional timbers, both in the production process and in their application as spanning members. A literature review by MacKinnon found historical and more recent work on round wood, but scant mention of puncheons. A purely geometric assessment of kerfs and slabs compared sawmill wastes and performance of laminated lumber and puncheon slabs. Goldsmith’s M.Arch thesis on forest-informed design points out that irrespective of structural performance, the additional mass conserved in puncheons sequesters carbon. Nonetheless, we built a specially designed apparatus to begin assessing actual loss of stiffness entailed in progressive sawing: load testing was carried out by Reay and Roworth. We also built a puncheon bridge and other structures to explore the tectonic and expressive potential of this construction. Positive results in most areas of investigation suggest further work be undertaken.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".