Bibliographic record
Abstract
STUDY DESIGN: A cross-sectional autopsy study. OBJECTIVE: This study investigated the prevalence of endplate lesions, classified them on the basis of morphological features, and determined their distribution patterns through direct measurements of cadaveric spines as well as examining their associations with age. SUMMARY OF BACKGROUND DATA: Endplate lesions may play a role in disc degeneration and back pain; however, related research has been rare. While Schmorl's nodes have received some attention, other endplate pathologies have been largely ignored. A systematic study of endplate lesions is needed to reveal the types and prevalence of lesions present in the adult lumbar spine. METHODS: We studied 1148 vertebral endplates (L1-S1) from the cadaveric spines of 136 men (mean age, 52 yr). On the basis of morphological characteristics, 4 types of endplate lesions were identified, including Schmorl's nodes, fracture, erosion, and calcification. The lesion location, size, and involved endplate components were evaluated to depict their distribution patterns. The associations between endplate lesion findings and age were also examined. RESULTS: Endplate lesions were found in 45.6% of lumbar vertebral endplates. Schmorl's nodes were the most common and usually were small, located centrally, and most common in the upper lumbar region. Erosion and calcification lesions were relatively large and most common in the lower lumbar region. The presence of lesions on 1 endplate of the disc was associated with presence of lesions on the opposing endplate (odds ratio = 8.0, P < 0.001). Greater age was associated with the presence of each type of endplate lesion. CONCLUSION: Endplate lesions are common and tend to affect both adjacent endplates of a disc simultaneously. The distribution patterns of the various types of endplate lesions differ, suggesting that they may have different pathogenic origins. Age or associated factors may play an important role in the pathogenesis of endplate lesions.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".