Bibliographic record
Abstract
SIGNIFICANCE: Skin exhibits direction-dependent biomechanical behavior, influenced by the structural orientation of its collagen-rich fibrous network and its viscous ground-substance matrix. Injury can affect the skin's structure and composition, thereby greatly influencing the biomechanics and directionality of the resulting scar tissue. RECENT ADVANCES: A combination of stress-relaxation and tensile failure testing identifies both the tissue's physiologically relevant viscoelastic behavior and resistance to rupture. When studied in mutually orthogonal directions in the plane of the tissue, these measures give insight into the directional properties of healthy tissue, and how they change with injury. By controlling the biomechanics of the wound environment, a new force-modulating dressing has demonstrated the ability to improve healing and reduce scar formation. CRITICAL ISSUES: Skin and scar biomechanics are typically characterized by using tensile failure, which identifies the tissue's resistance to rupture but offers limited insight into its normal daily function. Characterizing physiologically relevant biomechanics of skin, and how they change with injury, is critical to understand the tissue's ability to resist elongation, bear load, and dissipate energy via viscous means. FUTURE DIRECTIONS: Compared with uninjured skin, scar tissue demonstrates similar high-load stiffness, greatly reduced resistance to failure, reduced low-load compliance, and altered material directionality. These findings, identified through combined stress relaxation and failure testing, suggest morphological changes with injury that are consistent with the viscoelastic and directional changes observed biomechanically. A more complete understanding of the directional, physiologically relevant skin biomechanics can guide the design and critical functional assessment of wound treatments, scaffolds, and tissue-engineered skin replacements.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".