An intra‐bone axial load transducer: development and validation in an in‐vitro radius model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Accurate measurement of forces through the proximal radius can assess the effects of some surgical procedures on radioulnar load sharing, but is difficult to achieve given the redundant loading nature of the musculoskeletal system. Previously reported devices have relied on indirect measurements that may alter articular joint location and function. An axial load transducer interposed in the diaphysis of the radius may accurately quantify unknown axial loads of the proximal radius, and maintain articular location. METHODS: An in-vitro radius model was developed by interposing an axial load transducer in the diaphysis of the proximal radius. Static loads of 20, 40, 60, 80, and 100 N were applied with a servo-hydraulic actuator to the native radial head at angles of 10°, 20°, 30°, and 40° in the anterior, posterior, medial and lateral directions. FINDINGS: Linear regression of five repeatability trials showed excellent agreement between the transducer and applied loads (R (2) = 1 for all trials). For off-axis net joint loads, the majority of measured loading errors were within the inter-quartile range for mean loads up to 80 N. Loads below 80 N and outside the inter-quartile range had errors of less than 1 N. CONCLUSIONS: The repeatability and off-axis net joint load results of this study validate the effectiveness of the interposed axial load transducer to accurately quantify proximal radius loads. The surgical technique preserves the native articular location and soft-tissue constructs, like the annular ligament. The modular design allows for testing the effects of length-changing osteotomies in subsequent biomechanical studies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it