Bibliographic record
Abstract
The oral cavity hosts a variety of different fibroblast populations that are generally responsible for maintaining homeostasis of the soft connective tissue. In addition to regulating the turnover and structural arrangement of collagen and other proteins of the extracellular matrix, fibroblasts perform a number of specialized functions. Certain fibroblast subpopulations in the gingiva, oral mucosa and periodontal ligament serve as progenitor cells with multilineage differentiation and self-renewal characteristics. In the periodontal ligament, fibroblasts further appear to function as mechanosensing entities that regulate collagen-secretory and collagen-remodeling activities according to the level of strain in the ligament. Mechanical challenge also plays an important role during the activation of periodontal fibroblasts in response to injury. Dysregulation of this activation process can lead either to poor healing and chronic wounds or to overly healed wounds with fibrosis. This review will elaborate on the roles of mechanical factors and mechanoperception in fibroblast activation, the molecular features of activated fibroblasts and the regulation mechanisms of fibroblast contraction. Pharmacological interference at each level is currently being pursued to improve the outcome of healing of injured periodontal tissue.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".