Giant cell tumours in fingers among the Inuit population in Greenland
Bibliographic record
Abstract
OBJECTIVE: Giant cell tumours (GCTs) of the tendon sheets in fingers are rare. We therefore find it of interest to report on 5 cases identified in the Inuit population in Greenland within 16 months prior to this study. MATERIAL AND METHODS: The Inuit account for 56,000 people of the total population in Greenland. From November 2010 to 16 months prior to this study, we diagnosed 5 cases (0.6% of all orthopaedic operations) with a GCT of the flexor tendon sheet of a finger. The patients were aged between 10 and 54 years, and 4 were women. All of them had noticed slow-growing tumours over 3 or more years and were referred for a suspected ganglion. RESULTS: In two cases, the tumour was located at the distal interphalangeal (DIP) joint in the thumb and in one case at the third finger. Two other patients had tumours at the metacarpophalangeal (MCP) joint of the third finger and the thumb, respectively; one of these two had a communicating tumour to the DIP joint. The last patient had two tumours on the same finger, one at the MCP joint and the other at the DIP joint. In one case, the tumour had also eroded the cortex of the first phalanx of the thumb, and the largest tumour measured 5 cm. CONCLUSION: GCTs of the flexor tendon sheets in fingers are rare. It could be a coincidence that we have seen 5 cases within a short period of time. It is not possible to identify past cases through a register. A tumour in a finger is not the most common location for a ganglion, especially not at the DIP level. Therefore, a large tumour at this location is more likely to be a GCT.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".