The effect of excision of the radial head and metallic radial head replacement on the tension in the interosseous membrane
Bibliographic record
Abstract
We measured the tension in the interosseous membrane in six cadaveric forearms using an in vitro forearm testing system with the native radial head, after excision of the radial head and after metallic radial head replacement. The tension almost doubled after excision of the radial head during simulated rotation of the forearm (p = 0.007). There was no significant difference in tension in the interosseous membrane between the native and radial head replacement states (p = 0.09). Maximal tension occurred in neutral rotation with both the native and the replaced radial head, but in pronation if the radial head was excised. Under an increasing axial load and with the forearm in a fixed position, the rate of increase in tension in the interosseous membrane was greater when the radial head was excised than for the native radial head or replacement states (p = 0.02). As there was no difference in tension between the native and radial head replacement states, a radial head replacement should provide a normal healing environment for the interosseous membrane after injury or following its reconstruction. Load sharing between the radius and ulna becomes normal after radial head Replacement. As excision of the radial head significantly increased the tension in the interosseous membrane it may potentially lead to its attritional failure over time.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".