Characterizing Mineral Ellipsoids in New Bone Formation at the Interface of Ti6Al4V Porous Implants
Bibliographic record
Abstract
Abstract The hierarchy of newly formed bone contains elements of disorder within an ordered multiscale structure, spanning from the macroscale to below the nanoscale. With mineralized structures presenting in the shape of ellipsoids in mature and mineralizing tissue, this work characterizes the heterogeneity in the mineral ellipsoid packing at the interface of porous titanium implants. Using scanning transmission electron microscopy and plasma‐focused ion beam–scanning electron microscopy, mineral ellipsoids are characterized at the implant interface in both 2D and 3D. Heterogeneous in their size and shape within the newly formed bone tissue, ellipsoids are observed with alternating orientations corresponding to unique lamellar packets within 23 µm of the titanium implant interface—although this motif is not universal, and a mineral‐dense zone can also appear at the implant interface. Short‐order ellipsoid orientation shifts are also present in the 3D probe of the implant interface, where a ≈90° misorientation angle between neighboring packets of mineral ellipsoids (and an intervening organic layer) resolves with increasing distance from the titanium. Combined with local patches of woven‐to‐lamellar transition, the early heterogeneity and transformation of peri‐implant bone structure is a quintessential step in the development of a functional connection between implant and bone.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".