Case 1: Flexion contracture of the hand / Case 2: Immediate breast reconstruction
Bibliographic record
Abstract
Flexion contracture of the hand a 71-year-old man presents with flexion contractures of his left ring and small metacarpal-phalangeal joints and complains of difficulty with piano playing, sporting activities and hygiene.Objective 1: The candidate can formulate a provisional diagnosis.Question 1: What is your provisional diagnosis?Key Answers 1: Dupuytren's contracture/palmar fibromatosis Objective 2: The candidate can take an appropriate history Question 2: What information would be important to obtain when taking a history from this patient?Key Answers 2: Onset and progression of disease Involvement of other areas (contralateral hand, feet, penis, etc) Prior interventions -nonoperative or operative Comorbidities or risk factors (diabetes mellitus, HIV infection, epilepsy, smoking) Objective 3: The candidate can develop a management plan Question 3: The patient informs you that he has previously had surgical excision of disease in his ring finger.That surgery was approximately 5 years ago and he first noticed recurrence approximately 2 years ago.He has noticed progressive difficulty with sporting activities, playing the piano, and hand hygiene.What are the options for managing this patient?Key Answers 3: Revision partial palmar fasciectomy with or without skin grafting Collagenase injection (Xiaflex) Needle aponeurotomy -likely not recommended given history of prior exicision and severity of contracture.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".