Carpal kinematics and morphological correlates of wrist ulnar deviation mobility in nonhuman anthropoid primates
Bibliographic record
Abstract
OBJECTIVES: Primates employ wrist ulnar deviation during a variety of locomotor and manipulative behaviors. Extant hominoids share a derived condition in which the ulnar styloid process has limited articulation or is completely separated from the proximal carpals, which is often hypothesized to increase ulnar deviation range of motion. Acute angulation of the hamate's triquetral facet is also hypothesized to facilitate ulnar deviation mobility and mechanics. In this study, we test these longstanding ideas. METHODS: Three-dimensional (3D) carpal kinematics were examined using a cadaveric sample of Pan troglodytes, Pongo sp., and five monkey species. Ulnar styloid projection and orientation of the hamate's triquetral facet were quantified using 3D models. RESULTS: Although carpal rotation patterns in Pan and Pongo were uniquely similar in some respects, P. troglodytes exhibited overall kinematic similarity with large terrestrial cercopithecoids (Papio and Mandrillus). Pongo, Macaca, and Ateles had high wrist ulnar deviation ranges of motion, but Pongo did this via a unique mechanism. In Pongo, the triquetrum functions as a distal carpal rather than part of the proximal row. Ulnar styloid projection and wrist ulnar deviation range of motion were not correlated but ulnar deviation range of motion and the triquetrohamate facet orientation were correlated. CONCLUSIONS: Increased ulnar deviation mobility is not the function of ulnar styloid withdrawal in hominoids. Instead, this feature probably reduces stress on the ulnar side wrist or is a byproduct of adaptations that increase supination. Orientation of the hamate's triquetral facet offers some potential to reconstruct ulnar deviation mobility in extinct primates.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".