In-Vivo Corrosion Characterization and Assessment of Absorbable Metal Implants
Bibliographic record
Abstract
Absorbable metals have been introduced as materials to fabricate temporary medical implants. Iron, magnesium and zinc have been considered as major base elements of such metals. The metallurgical characterization and in-vitro corrosion assessment of these metals have been covered by the new ASTM standards F3160 and F3268. However, the in-vivo corrosion characterization and assessment of absorbable metal implants are not yet well established. The corrosion of metals in the in-vivo environment leads to metal ion release and corrosion product formation that may cause excessive toxicity. The aim of this work is to introduce the techniques to assess absorbable metal implants and their in-vivo corrosion behavior. This contains the existing approaches, e.g., implant retrieval and histological analysis, ultrasonography and radiography, and the new techniques for real-time in-vivo corrosion monitoring.
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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 | 0.001 | 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".