Bibliographic record
Abstract
The development of biomaterials A biomaterial has been defined by Hench and Erthridge as a synthetic material used to replace a part or a function of the body in a safe, reliable, economic and physiologically acceptable manner. The Celmson University Advisory Board for Biomaterials has formally defined a biomaterial to be “a systemically and pharmacologically inert substance designed for implantation within or in a medical device, intended to interact with biological systems.” Biomaterials have been widely used in many areas, including replacement of damaged parts (artificial hip), assisting in healing (sutures), improving biological functions (pacemaker, contact lens), correcting abnormalities (spinal rods), cosmetics (augmentation mammoplasty), aiding diagnoses (probes) and aiding treatment (catheters). A material is considered biocompatible if it causes no irritation, allergic or toxic responses when used in a biological system [1]. Table 7.1 provides some examples of biomaterials used in the body. Biotechnology and nanotechnology are the two of twenty-first century's most promising technologies. Convergence of these two technologies is expected to create innovations and play a vital role in various biomedical applications. The symposium in 2000 entitled “Nanoscience and Technology: Shaping Biomedical Research” held by the National Institutes of Health Bioengineering Consortium (BECON) addressed eight areas of nanoscience and nanotechnology, which include synthesis and use of nanostructures, applications of nanotechnology to therapy, biomimetic and biologic nanostructures, electronic–biology interface, devices for early detection of disease, tools for the study of single molecules, nanotechnology and tissue engineering [2].
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".