Strategic Design and Fabrication of Engineered Scaffolds for Articular Cartilage Repair
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Damage to articular cartilage can eventually lead to osteoarthritis (OA), a debilitating, degenerative joint disease that affects millions of people around the world. The limited natural healing ability of cartilage and the limitations of currently available therapies make treatment of cartilage defects a challenging clinical issue. Hopes have been raised for the repair of articular cartilage with the help of supportive structures, called scaffolds, created through tissue engineering (TE). Over the past two decades, different designs and fabrication techniques have been investigated for developing TE scaffolds suitable for the construction of transplantable artificial cartilage tissue substitutes. Advances in fabrication technologies now enable the strategic design of scaffolds with complex, biomimetic structures and properties. In particular, scaffolds with hybrid and/or biomimetic zonal designs have recently been developed for cartilage tissue engineering applications. This paper reviews critical aspects of the design of engineered scaffolds for articular cartilage repair as well as the available advanced fabrication techniques. In addition, recent studies on the design of hybrid and zonal scaffolds for use in cartilage tissue repair are highlighted.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it