Arthroscopic anatomy of the subdeltoid space
Bibliographic record
Abstract
From the first shoulder arthroscopy performed on a cadaver in 1931, shoulder arthroscopy has grown tremendously in its ability to diagnose and treat pathologic conditions about the shoulder. Despite improvements in arthroscopic techniques and instrumentation, it is only recently that arthroscopists have begun to explore precise anatomical structures within the subdeltoid space. By way of a thorough bursectomy of the subdeltoid region, meticulous hemostasis, and the reciprocal use of posterior and lateral viewing portals, one can identify a myriad of pertinent ligamentous, musculotendinous, osseous, and neurovascular structures. For the purposes of this review, the subdeltoid space has been compartmentalized into lateral, medial, anterior, and posterior regions. Being able to identify pertinent structures in the subdeltoid space will provide shoulder arthroscopists with the requisite foundation in core anatomy that will be required for challenging procedures such as arthroscopic subscapularis mobilization and repair, biceps tenodesis, subcoracoid decompression, suprascapular nerve decompression, quadrangular space decompression and repair of massive rotator cuff tears.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".