In vitro bioactivity of 3D Ti-mesh with bioceramic coatings in simulated body fluid
Bibliographic record
Abstract
3D Ti-mesh has been coated with bioceramics under different coating conditions, such as material compositions and micro-porosity, using a dip casting method. Hydroxyapatite (HA), micro-HA particles (HAp), a bioglass (BG) and their different mixtures together with polymer additives were used to control HA-coating microstructures. Layered composites with the following coating-to-substrate designs, such as BG/Ti, HA + BG/BG/Ti and HAp + BG/BG/Ti, were fabricated. The bioactivity of these coated composites and the uncoated Ti-mesh substrate was then investigated in a simulated body fluid (SBF). The Ti-mesh substrate and BG/Ti composite did not induce biomimetic apatite deposition when they were immersed in SBF for the selected BG, a pressable dental ceramic, used in this study. After seven days in SBF, an apatite layer was formed on both HA + BG/BG/Ti and HAp + BG/BG/Ti composites. The difference is the apatite layer on the HAp + BG/BG/Ti composite was rougher and contained more micro-pores, while the apatite layer on the HA + BG/BG/Ti composite was dense and smooth. The formation of biomimetic apatite, being more bioresorbable, is favored for bone regeneration.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".