Anatomical Course Demarcating the Safe Area for the Superior Gluteal Nerve
Bibliographic record
Abstract
Iatrogenic injury to the superior gluteal nerve (SGN) persists despite a safe area being defined. Current descriptions of the course of the SGN are conflicting and do not provide agreeable distances to surface landmarks that are useful for most health care professionals. This study aimed to suggest a more conservative and gender-dependent estimate of the safe area between each buttock and genitals as defined by four bony surface landmarks. The posterior and lateral surfaces of each buttock in eight cadavers, four male and four female, were dissected. The surface anatomy of sixteen SGNs was defined in relation to the quadrate tubercle of the intertronchanteric crest of the femur (QTIF), the most cranial ridge of the iliac crest (IC), the anterior superior iliac spine (ASIS) and the posterior superior iliac spine (PSIS). Between the sexes, no significant difference existed concerning average SGN lengths across each buttock pair, (i.e. SGN length male/female difference df=3 (p=0.273); Pearson = - 0.76). There was no significant difference between both buttock sides concerning the SGN distances from each of the four bony surface landmarks across either sex (e.g. male QTIF df=3 (p=0.284); Pearson correlation = -0.31.) From our measurements we conclude that the standard safe area is too generous and should be half the size immediately adjacent to the tip of the greater trochanter.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".