Special Issue on Advances in Biomedical Materials Science and Technology
Bibliographic record
Abstract
The research and development of biomaterials composed of metallic and other materials are receiving much attention.Globally, there has been an increase in the aging population; however, this problem is particularly noticeable in Japan, which has come to be known as a super aging society.In such societies, there are a number of people with failed or lost bio-functionalities, necessitating the development of highly functional implants or health care goods.Therefore, new research and development on bio-functionalization or mechanical functionalization, fabrication technologies, evaluation of the in vivo or vitro bio-compatibility of structural biomaterials used for constructing implants, and furthermore an understanding of tissue structures to which biomaterials are applied are highly important.Ti-2015, the 13 th World Conference on Ti, was held from August 16 to 20, 2015 at San Diego, USA.The 10 th World Biomaterials Congress was held from May 17-22, 2016, at Montreal in Canada.Thermecʼ2016, International Conference on Processing and Manufacturing of Advanced Materials, also was held May 29 to June 3, 2016 at Graz in Austria.In these international conferences, a large number of topics concerning metallic structural biomaterials and other kinds of structural biomaterials were presented.In light of this, this special issue invites overviews and original technical papers on the design and development of structural biomaterials including biocompatible shape memory alloys or biodegradable biomaterials, and bio-functionalization by surface modi cations, powder metallurgy including accumulated manufacturing, wrought processing, corrosion behaviors, mechanical and biological bio-compatibility of biomaterials, and furthermore characteristics of tissues to which biomaterials are applied.In this special issue, totally 19 papers on metallic biomaterials including Ti, Co-Cr-Mo, Mg, Zr and TiNi alloys, and stainless steels including their fabrication processes, mechanical property evaluations, surface modi cations, cytocompatibility, animal testing, etc., antibacterial invert glasses, and ultrahigh-molecular-polyethylene knee components are included.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.091 | 0.042 |
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".