Bibliographic record
Abstract
BACKGROUND: Keloids are benign fibroproliferative tumors that extend beyond the original wound. Spontaneous keloids are those that result without a significant history of trauma. There are multiple reported cases in the literature. OBJECTIVE: This article provides a summary and review of the cases that have been reported with spontaneous keloids and organizes them according to their associated medical conditions. METHODS: A literature review was conducted using PubMed and MEDLINE that included all English published cases and case series from May 1955 to February 2018. RESULTS: Spontaneous keloids have been reported mainly in association with syndromes such as Rubinstein-Taybi syndrome, Dubowitz syndrome, Noonan syndrome, Goeminne syndrome, Bethlem myopathy, conjunctivocorneal dystrophy, X-linked recessive polyfibromatosis and a novel X-linked syndrome with flamin A mutation. Furthermore, spontaneous keloids were reported in atopic patients and a couple of patients who are medically healthy. CONCLUSION: Spontaneous keloids are diagnosed clinically based on the patient's history, and it is challenging to confirm since they might be triggered by minimal injury or inflammation especially if it is a single lesion. Reported syndromes indicate a genetic possibility in the pathogenesis of spontaneous keloids.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".