Special issue featuring articles from the 3rd International Symposium on Advanced Biomaterials and Biomechanics
Bibliographic record
Abstract
I felt very privileged when I was invited to put together this special issue of Biomedical Materials: Materials for Tissue Engineering and Regenerative Medicine , dedicated to advanced biomaterials. This topic was the subject of the 3rd International Symposium on Advanced Biomaterials and Biomechanics (ISAB 2 2005) held in Montreal on 3–6 April 2005. ISAB 2 2005 mainly focused on emerging biomaterials as well as recent developments in biomechanics, including their applications in the development of medical devices. As everybody knows, the field of biomedical materials and medical devices is a dynamic and a rapidly expanding discipline that addresses the fundamental and the engineering aspects of materials used in biology and medicine. The growing field of applications of biomedical materials ranges from the replacement of body parts and tissue engineering to drug delivery and gene therapy. In the post-genomic era, the potential for both regenerative medicine and nanomedicine is immense and they have become two of the most rapidly developing fields in biomedical research. A total of 228 papers (154 oral presentations and 74 poster presentations) were presented during the ISAB 2 symposium. We are very proud to say that we had several high profile representatives of the field (six keynote speakers and seven guest speakers). To accommodate all accepted papers, the scientific program was organized into 30 sessions covering most of the aspects of advanced biomaterials/biomechanics. The topics presented a range from bio/nanomaterials, smart materials/devices, bioceramics and bioglasses, sterilisation of medical devices, cell encapsulation, nanotubes, porous biomaterials, artificial muscles, and tissue engineering. Also, recent advances in locomotion system analysis, biomechanical modeling, ligaments and joint evaluation, spinal biomechanics and fluid biomechanics were discussed. The symposium was very successful and was highly appreciated by the attendees and participants. It is particularly delightful to know that distinguished researchers have contributed their excellent papers to make a special issue on biomedical materials. We would like to express our thanks to all the authors for submitting their work to this special issue. We also acknowledge the contributions of the referees who participated in the review process. The encouragement and assistance of Professors F-Z Cui, I-S Lee and M Spector, Editors-in-Chief of Biomedical Materials , as well as the discussions we had, are greatly appreciated. We hope that researchers in the field of biomedical materials will find the papers in this special issue useful.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.105 | 0.045 |
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".