Development and validation of a finite element model to simulate the opening of a medial opening wedge high tibial osteotomy
Bibliographic record
Abstract
© 2018 Arthroscopy Association of North America Significant focus has recently been placed on the contribution of the anterolateral ligament (ALL) to controlling anterolateral rotatory laxity of the anterior cruciate ligament (ACL) injured knee. Many recent studies have investigated the use of magnetic resonance imaging and ultrasound on determining the degree of ALL injury and whether this is correlated to high-grade rotatory laxity. Unfortunately, most studies lack a reference standard, and as such it is challenging to determine whether it truly is the ALL that is injured or if the capsule-osseous layer and deep iliotibial band are involved. Historic literature has demonstrated the importance of these other structures having been noted to be injured at the time of ACL reconstruction. As such, it is clear that high-grade rotatory laxity does not result from an isolated ACL injury. We therefore must remain open to the idea that it is not just the ALL that may cause this injury pattern, and optimal solutions to address this patholaxity have yet to be fully determined.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".