Relative Contributions of Chemistry and Topography to the Osseointegration of Hydroxyapatite Coatings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of the current study was to ascertain the relative contributions of surface chemistry and topography to the osseointegration of hydroxyapatite-coated implants. A canine femoral intramedullary implant model was used to compare the osseous response to commercially pure titanium implants that were either polished, grit-blasted, plasma-sprayed with hydroxyapatite, or plasma-sprayed with hydroxyapatite and masked with a very thin layer of titanium using physical vapor deposition (titanium mask). The titanium mask isolated the chemistry of the underlying hydroxyapatite layer without functionally changing its surface topography and morphologic features. At 12 weeks, the bone-implant specimens were prepared for undecalcified thin section histologic evaluation and serial transverse sections were quantified with backscattered scanning electron microscopy for the percentage of bone apposition to the implant surface. Bone apposition averaged 3% for the polished implants and 23% for the grit-blasted implants. Bone apposition to the hydroxyapatite-coated implants averaged 74% whereas bone apposition to the titanium mask implants averaged 59%. Although there was significantly greater osseointegration with the hydroxyapatite-coated implants, 80% of the maximum bone forming response to the implant surfaces developed with the titanium mask implants. This simple, controlled experiment revealed that topography is the dominant factor governing bone apposition to hydroxyapatite-coated implants.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it