Miniscrews for orthodontic anchorage: nanoscale chemical surface analyses
Bibliographic record
Abstract
OBJECTIVES: The goal of this study was to determine the chemical composition of the passivation layer of three clinically available orthodontic miniscrews at different depths. MATERIALS AND METHODS: The miniscrews used were Aarhus Mini-Implant (AAR), IMTEC Ortho (IMT), and VectorTAS (VEC). The chemical compositions of the as-received miniscrews were determined by X-ray photoelectron spectroscopy (XPS). Data was acquired before etching the miniscrews with argon, as well as after etching at depths of 10 nm, 20 nm, 30 nm, and 80 nm. RESULTS: The elements found in all miniscrews were mainly C, O, and Ti. Also found were other metals in small amounts, and other trace elements. All three miniscrews showed very different characteristics in surface composition. IMT had the greatest increase in Ti, as well as the most titanium metal at 80 nm. VEC remained stable at all tested depths and contained no titanium metal at 80 nm. AAR was an intermediate between the two. CONCLUSIONS: The passivation layer of the orthodontic miniscrews has different compositions depending on the brand, as well as the depth analyzed. VEC appeared to have the largest passivation layer, and IMT appeared to have the thinnest passivation layer.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".