Functional and Anatomic Orientation of the Femoral Head
Bibliographic record
Abstract
BACKGROUND: Femoral neck geometry directly affects load transmission through the hip. Orientations may be described anatomically or using functional definitions that consider load transmission. QUESTIONS/PURPOSES: This study introduces and applies a new method for characterizing functional femoral orientation based on the distribution of subchondral bone density in the femoral head and compares it with orientation measures generated via established anatomic landmark-based methods. Both orientation methods then are used to characterize side-to-side symmetry of orientation and differences between men and women within the population. PATIENTS AND METHODS: A retrospective review of CT imaging data from 28 patients was performed. Anatomic orientation was determined using established two-dimensional and three-dimensional landmarking methods. Subchondral bone density maps were generated and used to define a density-weighted surface normal vector. Orientation angles generated by the three methods were compared, with side-to-side symmetry and differences between genders also investigated. RESULTS: The three methods measured substantially different angles for anteversion and neck-shaft angle. Weak correlations were found between anatomic and functional orientation measures for neck-shaft angle only. CONCLUSIONS: Neck-shaft angles calculated using the functional orientation method corresponded well with previous in vivo loading data. An absence of strong correlation between functional and anatomic measures reinforces the concept that bone geometry is not solely responsible for determining loading of the femoral head. LEVEL OF EVIDENCE: Level II, Diagnostic Studies--Investigating a Diagnostic Test. See the Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".