Plant Fibers as Composite Reinforcements for Biomedical Applications
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
Plant fibers possess high strength, high fracture toughness and elasticity, and have proven useful because of their diversity, versatility, renewability, and sustainability. For biomedical applications, these natural fibers have been used as reinforcement for biocomposites to infer these hybrid biomaterials mechanical characteristics, such as stiffness, strength, and durability. The reinforced hybrid composites have been tested in structural and semi-structural biodevices for potential applications in orthopedics, prosthesis, tissue engineering, and wound dressings. This review introduces plant fibers, their properties and factors impacting them, in addition to their applications. Then, it discusses different methodologies used to prepare hybrid composites based on these widespread, renewable fibers and the unique properties that the obtained biomaterials possess. It also examines several examples of hybrid composites and their biomedical applications. Finally, the findings are summed up and some thoughts for future developments are provided. Overall, the focus of the present review lies in analyzing the design, requirements, and performance, and future developments of hybrid composites based on plant fibers.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 | 0.002 |
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