Bibliographic record
Abstract
Background: Mouthguards (MGs) remain an important piece of personal protection for athletes for the prevention of injury. Although MGs provide tremendous benefits, the design and fabrication process does not record the position of the mandible or the occlusion, which could lead to injury. This study compared a novel MG to over-the-counter (OTC) and custom MGs on a skull model. Methods: The OTC MG was formed as per manufacturer's guidelines, the custom MG was laboratory fabricated, and the novel MG was fabricated through a proprietary process. Each group of the three MGs was assessed for vertical dimension change, occlusal contacts, and condylar displacement. Results: Average number of occlusal contacts for the OTC, custom and novel MG were 2.4, 4.0, and 10, respectively. There was a significant difference between all values (P < 0.05). Average change in vertical dimension for the OTC, custom, and novel MG were 15.3 mm, 9.3 mm, and 8.0 mm, respectively. The novel MG value was significantly different (P < 0.05). The average distance of condylar displacement for the OTC, custom and novel MG were 1.9 mm, 1.3 mm and 0.6 mm, respectively. Conclusions: The novel MG was significantly different (P < 0.05). The data from this preliminary investigation suggests that the novel mouthguard had maximized occlusal contacts, minimized vertical dimension change and condylar displacement as compared to OTC and custom MGs.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".