Polyethnic/Racial Differences in the Anatomy of Anterior Femoral Curvature: Orthopedic Consideration
Bibliographic record
Abstract
T. Dale Stewart (1962) was the first to quantitatively examine the anterior femoral curvature differences seen in polyethnic/racial populations. Previous studies described the curvature as anteriorly convex in the sagittal plane. Differences in sagittal femoral bowing (SFB) have considerable implications for the survivability of total knee arthroplasty prostheses. This qualitative and quantitative study examined SFB anatomy of three distinct ethnic groups: contemporary European and African populations and archeological pre‐European contact Ipiutak (500 BCE – 500 CE) Inuit populations. The intensity of curvature (IC) and its position on the bone was taken using Walensky (1965) methods of analysis. IC was determined by the difference between the height of the sighted maximum point of curvature (MPC) and the proximal low point of the diaphysis. The position of the MPC was determined as a ratio of the difference in distance from the MPC to the proximal diaphysial low point, and the diaphysial length. Results indicate that although the MPC occurs in the mid‐third of the diaphysial shaft regardless of race, the IC in the Inuit sample is significantly greater than that of the European and Africans (p<0.05). CT digital analysis revealed that the greatest amount of bowing occurred in the plane of torsion rather than in the sagittal plane. Using the oblique plane would reveal the true bowing intensity that is otherwise masked by traditional morphometrics. These preliminary data suggest the accentuated oblique bowing is directly correlated with femoral torsion, requiring racial consideration in orthopedic surgical strategies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".