Advances in Multiscale Characterization Techniques of Bone and Biomaterials Interfaces
Bibliographic record
Abstract
The success of osseointegrated biomaterials often depends on the functional interface between the implant and mineralized bone tissue. Several parallels between natural and synthetic interfaces exist on various length scales from the microscale toward the cellular and the atomic scale structure. Interest lies in the development of more sophisticated methods to probe these hierarchical levels in tissues at both biomaterials interfaces and natural tissue interphases. This review will highlight new and emerging perspectives toward understanding mineralized tissues, particularly bone tissue, and interfaces between bone and engineered biomaterials at multilength scales and with multidimensionality. Emphasis will be placed on highlighting novel and correlative X-ray, ion, and electron beam imaging approaches, such as electron tomography, atom probe tomography, and in situ microscopies, as well as spectroscopic and mechanical characterizations. These less conventional approaches to imaging biomaterials are contributing to the evolution of the understanding of the structure and organization in bone and bone integrating materials.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".