Latissimus dorsi tendon transfer for irreparable tears of the rotator cuff
Bibliographic record
Abstract
Latissimus dorsi tendon transfer (LDTT) is technically challenging. In order to clarify the local structural anatomy, we undertook a morphometric study using six complete cadavers (12 shoulders). Measurements were made from the tendon to the nearby neurovascular structures with the arm in two positions: flexed and internally rotated, and adducted in neutral rotation. The tendon was then transferred and measurements were taken from the edge of the tendon to a reference point on the humeral head in order to assess the effect of a novel two-stage release on the excursion of the tendon. With the shoulder flexed and internally rotated, the mean distances between the superior tendon edge and the radial nerve, brachial artery, axillary nerve and posterior circumflex artery were 30 mm (26 to 34), 28 mm (17 to 39), 21 mm (12 to 28) and 15 mm (10 to 21), respectively. The mean distance between the inferior tendon edge and the radial nerve, brachial artery and profunda brachii artery was 18 mm (8 to 27), 22 mm (15 to 32) and 14 mm (7 to 21), respectively. Moving the arm to a neutral position reduced these distances. A mean of 15 mm (8 to 21) was gained from a standard soft-tissue release, and 32 mm (20 to 45) from an extensile release. These figures help to define further the structural anatomy of this region and the potential for transfer of the latissimus dorsi tendon.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".