Polymer-Based Materials Built with Additive Manufacturing Methods for Orthopedic Applications: A Review
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
Over the last few decades, polymers and their composites have shown a lot of promises in providing more viable alternatives to surgical procedures that require scaffolds and implants. With the advancement in biomaterial technologies, it is possible to overcome the limitations of current methods, including auto-transplantation, xeno-transplantation, and the implantation of artificial mechanical organs used to treat musculoskeletal conditions. The risks associated with these methods include complications, secondary injuries, and limited sources of donors. Three-dimensional (3D) printing technology has the potential to resolve some of these limitations. It can be used for the fabrication of tailored tissue-engineering scaffolds, and implants, repairing tissue defects in situ with cells, or even printing tissues and organs directly. In addition to perfectly matching the patient’s damaged tissue, printed biomaterials can have engineered microstructures and cellular arrangements to promote cell growth and differentiation. As a result, such biomaterials allow the desired tissue repair to be achieved, and could eventually alleviate the shortage of organ donors. As such, this paper provides an overview of different 3D-printed polymers and their composites for orthopedic applications reported in the literature since 2010. For the benefit of the readers, general information regarding the material, the type of manufacturing method, and the biomechanical tests are also reported.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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