Bibliographic record
Abstract
BACKGROUND: Raynaud's phenomenon occurs among automobile mechanics secondary to long-term use of vibrating hand-held tools. It can also occur from traumatic injury to the upper extremity. AIM: This report describes a case of single digit Raynaud's phenomenon in an automobile mechanic due to focal arterial impact trauma. CASE REPORT: A 38-year-old right-handed transmission mechanic complained of paraesthesia and blanching of the right index finger on exposure to cold and eventually developed a transient necrotic ulcer at the tip of the digit. He had a long history of occupational exposure to vibrating hand-held power tools. Evaluation for common causes of Raymond's phenomenon was negative. The diagnosis of hand-arm vibration syndrome (HAVS) was rejected because of the rapidity of progression and severity of the symptoms restricted only to the index finger without corresponding symptoms of the other digits of the right hand as would be expected. Angiography revealed an obstructive lesion of the distal right radial artery at the wrist and he was diagnosed with thenar hammer syndrome. This uncommon condition was due to focal injury of the distal radial artery caused by repeated slamming of transmission parts on a work table. CONCLUSIONS: Not all cases of Raynaud's phenomenon in workers using vibrating hand-held tools are due to HAVS. Alternative aetiologies should be considered especially if symptoms are asymmetrical and unilateral.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".