Bibliographic record
Abstract
Significance: Main dermal forms of fibroproliferative disorders are hypertrophic scars (HTS) and keloids. They often occur after cutaneous wound healing after skin injury, or keloids even form spontaneously in the absence of any known injury. HTS and keloids are different in clinical performance, morphology, and histology, but they all lead to physical and psychological problems for survivors. Recent Advances: Although the mechanism of wound healing at cellular and tissue levels has been well described, the molecular pathways involved in wound healing, especially fibrotic healing, is incompletely understood. Critical Issues: Abnormal scars not only lead to increased health-care costs but also cause significant psychological problems for survivors. A plethora of therapeutic strategies have been used to prevent or attenuate excessive scar formation; however, most therapeutic approaches remain clinically unsatisfactory. Future Directions: Effective care depends on an improved understanding of the mechanisms that cause abnormal scars in patients. A thorough understanding of the roles of chemokines in cutaneous wound healing and abnormal scar formation will help provide more effective preventive and therapeutic strategies for dermal fibrosis as well as for other proliferative disorders.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".