Superplastic Prosthetic Forming - <i>In Vitro</i> Response
Bibliographic record
Abstract
Steinemann, 1998 [1] reported an observation made several decades earlier in 1951, by Leventhal [2] in which ‘bone reaction was studied by the insertion of up to 80 titanium screws into the femora of rats. At the end of sixteen weeks the screws were so tight that in one specimen the femur was fractured when an attempt was made to remove the screw’. Consequently, the main reasons given for the suitability of titanium for surgical implantation are its strength, its failure to cause tissue reaction, and the fact that bone becomes attached to titanium. Now, we call this attachment osseointegration which is considered to be the direct structural and functional connection between living bone and the surface of a load-bearing artificial implant. However, osseointegration is not considered to be a chemical bond between titanium and bone. Implant materials that actually bond to bone are considered to be bioactive. Materials for clinical use can be classified into three categories: resorbable, bioactive and nearly inert materials. A bioactive material is defined as a material that elicits a specific biological response at the interface of the material, which results in the formation of a bond between the tissue and that material. Whereas specific bioceramics are considered to be bioactive, titanium alloys are not normally considered to be so. However, recent surface modification of titanium alloys provide evidence that titanium alloys can become bioactive after treatment with NaOH and the ensuing development of a titanate gel on the metal surface.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".