Strain pattern in the upper facial skeleton: Preliminary model development
Bibliographic record
Abstract
In the human upper facial skeleton, the patterns of strain caused by physiological loading are not known. It is generally accepted that these patterns can be predicted based on the morphology of the bone, but this is not necessarily the case. The elucidation of these patterns of strain has a significant impact on the plating techniques of facial fractures, the development of bone substitutes and tissue-engineered bone, and the understanding of facial development. The goal of this study was to initiate the development of a model that could be used to measure strain magnitude and direction in the upper facial skeleton from physiological loading of facial musculature. A strain gauge was bonded to the lateral orbital rim of a cadaveric skull that had been dissected, leaving only muscular origins and insertions intact. Braided nylon straps were sutured to the origins and insertions of the masseter and levator labii superioris, and these were pulled individually using a hydraulic testing machine. When the masseter origin was pulled, the recorded strain increased with increasing force and the angle of the strain corresponded directly to the angle of pull. When the levator labii superioris origin was pulled, the angle of strain was directed anteriorly and inferiorly, but did not correspond with the axis of the muscle or the axis of the lateral orbital rim where the strain gauge was located. It was concluded that this model is reliable and reproducible for investigating strain magnitude and direction in the human upper facial skeleton.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".