Morphological and postural sexual dimorphism of the lumbar spine facilitates greater lordosis in females
Bibliographic record
Abstract
Previous work suggests females are evolutionarily adapted to have greater lumbar lordosis than males to aid in pregnancy load-bearing, but no consensus exists. To explore further sex-differences in the lumbar spine, and to understand contradictions in the literature, we conducted a cross-sectional retrospective study of sex-differences in lumbar spine morphology and sacral orientation. In addition, our sample includes data for separate standing and supine samples of males and females to examine potential sex-differences in postural loading on lumbosacral morphology. We measured sagittal lumbosacral morphology on 200 radiographs. Measurements include: lumbar angle (L1-S1), lumbar vertebral body and disc wedging angles, sacral slope and pelvic incidence. Lumbar angle, representative of lordotic curvature between L1 and S1, was 7.3° greater in females than males, when standing. There were no significant sex-differences in lumbar angle when supine. This difference in standing lumbar angle can be explained by greater lordotic wedging of the lumbar vertebrae (L1-L5) in females. Additionally, sacral slope was greater in females than males, when standing. There were no significant sex-differences in pelvic incidence. Our results support that females have greater lumbar lordosis than males when standing, but not when supine - suggesting a potentially greater range of motion in the female spine. Furthermore, sex-differences in the lumbar spine appear to be supported by postural differences in sacral-orientation and morphological differences in the vertebral body wedging. A better understanding of sex-differences in lumbosacral morphology may explain sex-differences in spinal conditions, as well as promote necessary sex-specific treatments.
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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) | 0.000 | 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) | 0.006 | 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".