<i>In vitro</i> evaluation of nonrigid support systems for the equine metacarpophalangeal joint
Bibliographic record
Abstract
Metacarpophalangeal (MCP) joint extension is primarily resisted by the digital flexor tendons and suspensory ligament. A variety of external support techniques are used to protect these supporting structures from or after injury by resisting MCP joint extension, although not all are effective and/or practical for use in an exercising horse. In this study, 7 forelimbs were loaded in vitro to determine the effect of a simple gamgee bandage, a 3-layered bandage with and without a contoured palmar splint, a neoprene exercise boot, and an innovative carbon fibre composite exercise boot (Dalmar tendon support boot). There was no significant resistance to MCP joint extension by the gamgee or neoprene exercise boot. The 3-layered bandage had a significant (P<0.01) supporting effect at MCP angles of > or = 245 degrees, and when combined with the contoured splint at angles of > or = 230 degrees. The Dalmar tendon support boot resisted MCP extension at angles of > or = 245 degrees (settings 1 and 2) and > or = 225 degrees (setting 3). These data demonstrate that the contoured splint and the Dalmar tendon support boot (which is also easily fitted for use during exercise) are useful for the management of tendon/ligament injury and during rehabilitation.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".