Bibliographic record
Abstract
Normal motion of the proximal interphalangeal joint requires bony support, intact articular surfaces, unimpeded tendon gliding, and uncompromised integrity of the collateral ligaments and volar plate. Deficiency in any one of these structural requirements can lead to a loss of finger joint motion and decreased hand function. Once finger extension is lost, options include nonsurgical or surgical treatment. Nonsurgical treatment such as splinting or serial casting should be tried before attempting surgical intervention. When severe flexion deformity exists or the vascular status of the finger has been compromised, arthrodesis or amputation should be undertaken instead of procedures to regain motion. Surgical options for regaining motion include external fixators and open surgical release. Although they can lead to improved extension at the proximal interphalangeal joint, external fixators carry a risk of reduced finger flexion and pin site infection. Most clinical series of patients who have undergone surgical release document improvement in flexion contracture between 25 degrees to 30 degrees and a shift of the flexion/extension arc into a more functional range. Close follow-up after surgery is warranted, with frequent physical therapy and splinting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".