[CAN NATURAL SKIN CREASE PREDICT OUR PHALANX JOINT ALIGNMENT?]
Bibliographic record
Abstract
BACKGROUND: Proximal interphalangeal injury may result in malalignment of the phalanx axis of motion. In some instances, these fractures are treated with an external fixation method such as Suzuki-type fixation, during which the surgeon must perform X-rays to preserve the phalanx anatomical axis of motion. OBJECTIVES: To assess the correlation between the palmar skin crease and the joint axis of the proximal interphalangeal joint (PIPJ) of the fingers opposing the thumb to improve the surgeons' perioperative planning procedure. Also, we aim to ascertain whether sex, age, and handedness have affected our findings. METHODS: We performed a single-center prospective study in which information on 144 digits from 18 patients was gathered. Radiopaque stainless-steel wire was used to mark the palmar skin crease of the PIPJ and a series of X-rays were performed to assess the actual axis of the PIPJ correlating to the marked skin crease. RESULTS: Our study shows a positive correlation between Cobb angle finger 2 and 5 (r = .468, p < .05). Also, a positive correlation between Cobb angle finger 3 and finger 4 (r = .474, p < .05). No significant differences were found between age groups, and right and left hands. Finger 2 Cobb angle was significantly higher in females (F = 2.27, M = 1.49), p = .048. CONCLUSIONS: The study results support the hypothesis that the palmar proximal interphalangeal skin crease is positively correlated with the joint line axis measurement from which the axis of motion is formed. Our findings show homogeneity across age and hand-sidedness.
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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 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".