Relative Sagittal Alignment of the Medial and Lateral Articular Surfaces of the Tibial Plateau Using Radiographic Parameters: A Radiographic Cadaveric Study
Bibliographic record
Abstract
OBJECTIVES: To characterize anatomic slope (sagittal alignment) of medial and lateral articular surfaces of the tibial plateau using x-ray and computed tomography (CT). METHODS: Fluoroscopy was used to acquire "perfect" anteroposterior (AP) images of 8 cadaveric knees by tilting a C-arm through a 30-degree cranial/caudal arc in 0.5-degree increments. Five surgeons independently selected perfect AP images that most accurately profiled medial and lateral articular surfaces. Corresponding angles were used to define tangent subchondral structures on sagittal CT that were considered as dominant bony landmarks in a protocol to determine tibial slope on sagittal CT in 46 additional cadaveric knees. RESULTS: Mean perfect C-arm AP angles were 4.2 degrees ± 2.6 degrees posterior for the medial plateau and 5.0 degrees ± 3.8 degrees posterior for the lateral plateau. It was noted that images acquired within a range of angles (medial range, 1.8 degrees ± 0.7 degrees; lateral range, 3.9 degrees ± 3.8 degrees) rather than a single angle adequately profiled each compartment. Using the CT protocol, mean medial slope (5.2 degrees ± 2.3 degrees posterior; range, 0.9-11.5 degrees) was less than lateral slope (7.5 degrees ± 3.0 degrees posterior; range 0.6-12.5 degrees; P < 0.001) in 54 knees. The difference between medial and lateral slopes in any individual specimen ranged from 3.1 degree more medially to 6.8 degrees more laterally. No differences were noted between right and left knees in paired specimens. CONCLUSIONS: On average, tibial slope in the lateral plateau is slightly greater than that in the medial plateau, and variation exists between compartments across patients. Because tibial slope is similar between contralateral limbs, evaluating slope on the uninjured side can provide a template for sagittal plane reduction of tibial plateau fractures.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".