Bibliographic record
Abstract
Bend-a-rule is a physical tool and workflow that enables the robust acquisition of planar contours of 3D shape. Our work exemplifies the design of physical artifacts that subsequently aid in digital design and fabrication. Bend-a-rule is a ruler, fabricated by laser-cutting a periodic pattern on a rigid board. The ruler has unidirectional flexibility, and readily bends to conform to the shape of curved planar contours on physical 3D objects. We present a novel workflow, by which this curved planar contour can be digitally acquired from a single image of the physical ruler. The acquired contour is then used to design laser-cut accessory shapes that attach to physcial 3D objects along the digitally acquired contour. We describe the construction of Bend-a-rule, propose an automatic algorithm for the extraction of a to-scale, planar 3D curve from a Bend-a-rule image, evaluate the resulting curves in comparison to ground truth data, and show example physical 3D objects augmented using Bend-a-rule.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
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".