In Vitro Degradation of Absorbable Zinc Alloys in Artificial Urine
Bibliographic record
Abstract
Absorbable metals have potential for making in-demand rigid temporary stents for the treatment of urinary tract obstruction, where polymers have reached their limits. In this work, in vitro degradation behavior of absorbable zinc alloys in artificial urine was studied using electrochemical methods and advanced surface characterization techniques with a comparison to a magnesium alloy. The results showed that pure zinc and its alloys (Zn⁻0.5Mg, Zn⁻1Mg, Zn⁻0.5Al) exhibited slower corrosion than pure magnesium and an Mg⁻2Zn⁻1Mn alloy. The corrosion layer was composed mostly of hydroxide, carbonate, and phosphate, without calcium content for the zinc group. Among all tested metals, the Zn⁻0.5Al alloy exhibited a uniform corrosion layer with low affinity with the ions in artificial urine.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.006 | 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 teacher head, 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".