Advances in Collagen/Hydroxyapatite Composite Materials
Bibliographic record
Abstract
The annually necessary human bone grafts are in continuous grown due to the increasing of fractals, congenital and non-congenital diseases. Based on statistical reports (Murugan and Ramakrishna 2005), only in USA about 6.3 million fractures occur every year and about 550.000 of these require bone grafting. The most frequently fractures occur at the level of hip, ankle, tibia and fibula. Due to the higher physical effort, the men are more exposed to fracture than women (2.8% in the case of men comparing to 2.0% in the case of women). The number of fractures increases year by year and consequently many researchers from different research fields co-operate in order to develop new bone graft materials. Also, it is important to mention that, in the present, the bone diseases are overlapped only by hearth diseases. The history of bone grafting is starting in 1913 when Dr. D.E. Robertson assays a piece of cat’s bone and a piece of human bone for bone grafting into dogs (Gallie and Toronto 1914). The microscopic analysis of implanted graft after 20 days shows that the space between graft and living bone is filled with new cancellous bone. These early works made the premises for the development of the bone grafts. Due to the increasing of the necessarily bone grafts, autografts and allografts can not cover the overall need of bone grafts. For compensate this gap, artificial (synthetic) grafts are necessary and, consequently used. The use of synthetic grafts has some advantages versus allografts, autografts and xenografts: the possibility to obtain unlimited number/quantity of synthetic grafts, more safety use of artificial bone grafts without disease transmission risk, pain limitation by elimination of some secondary surgical intervention. The need of bone grafts materials lead to the synthesis of many kind of materials with different properties. Function of the nature of these materials and the relation between these grafts and the host tissue, these materials can be divided into 4 generations (Fig. 1). The components of the first generation of bone grafting biomaterials have remarkable mechanical properties but they are neither bioresorbable nor bioactive. More than, the use of these kind of bone grafts have limited lifetime (usually less than 10-15 years) and need to be extracted and replaced surgically. Some of the most representative biomaterials from the first generation of bone grafting biomaterials are: the iron, cobalt, chromium, titan or their alloys: steel (especially 316 L), cobalt or titan based alloys (Corces 2002; Corces and Garcia 2007) etc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".