Quantification of three-dimensional skin displacement artefacts on the equine tibia and third metatarsus
Bibliographic record
Abstract
Abstract Routine study of three-dimensional (3D) tarsal kinematics is hampered by errors due to the displacement of skin surface-tracking markers relative to the underlying bones. Reliable kinematics can be obtained with bone-fixed markers, but an accurate, non-invasive method would have more applications. Simultaneous kinematic data from skin-based and bone-fixed markers attached to the tibia and third metatarsus were collected from three trotting subjects. The motion of the skin-based markers was extracted relative to the underlying bone motion tracked using the bone-fixed markers. The 3D skin displacement patterns for the skin-based markers were parameterized using a truncated Fourier series model. These displacements were expressed in terms of the local coordinate system for each bone. Skin displacement artefacts were observed in all three axes of each bone segment, with the largest displacements occurring at the proximal tibia. The mean skin displacement amplitudes in the tibia were 6.7%, 3.2% and 10.5% of segment length, and for the third metatarsus were 2.6%, 1.4% and 3.8% of segment length, for the craniocaudal, mediolateral and longitudinal segment axes, respectively. Skin displacement patterns could be expressed concisely using the Fourier series model. Displacements were also consistent between subjects, which should allow them to be used as a basis for developing a correction procedure for 3D tarsal joint kinematics.
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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 | 0.000 | 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".