Quantification of mouse <i>in vivo</i> whole-body vibration amplitude from motion-blur using <i>x</i>-ray imaging
Bibliographic record
Abstract
Musculoskeletal effects of whole-body vibration on animals and humans have become an intensely studied topic recently, due to the potential of applying this method as a non-pharmacological therapy for strengthening bones. It is relatively easy to quantify the transmission of whole-body mechanical vibration through the human skeletal system using accelerometers. However, this is not the case for small-animal pre-clinical studies because currently available accelerometers have a large mass, relative to the mass of the animals, which causes the accelerometers themselves to affect the way vibration is transmitted. Additionally, live animals do not typically remain motionless for long periods, unless they are anesthetized, and they are required to maintain a static standing posture during these studies. These challenges provide the motivation for the development of a method to quantify vibrational transmission in small animals. We present a novel imaging technique to quantify whole-body vibration transmission in small animals using 280 μm diameter tungsten carbide beads implanted into the hind limbs of mice. Employing time-exposure digital x-ray imaging, vibrational amplitude is quantified based on the blurring of the implanted beads caused by the vibrational motion. Our in vivo results have shown this technique is capable of measuring vibration amplitudes as small as 0.1 mm, with precision as small as ±10 μm, allowing us to distinguish differences in the transmitted vibration at different locations on the hindlimbs of mice.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".