Bibliographic record
Abstract
The purpose of the current investigation was two-fold: (i) to describe the development of 3D printed prostheses using antibacterial filaments and (ii) to verify the antibacterial properties of the 3D printed prostheses. Three-dimensional printed finger prostheses were manufactured using PLACTIVETM antibacterial 3D printing filaments. Two adults with left index finger amputations at the proximal phalanx were fitted with a customized 3D printed finger prosthesis manufactured with an antibacterial filament. The manual gross dexterity was assessed during the Box and Block Test. Patient satisfaction was assessed using the Quebec User Evaluation of Satisfaction with assistive Technology (QUEST 2.0). Bacterial analysis of the 3D printed prostheses was performed by two independent laboratories against Staphylococcus aureus and Escherichia coli (ISO 22196). Two customized 3D printed partial finger prostheses were manufactured using a 3D printed antibacterial filament. The bacterial analysis showed that PLACTIVETM with 1% antibacterial nanoparticles additives was up to 99.99% effective against Staphylococcus aureus and Escherichia coli. The manual gross dexterity assessed was improved after using the 3D printed partial finger prosthesis. The research subjects indicated that they were “quite satisfied” to “very satisfied” with the 3D printed partial finger prosthesis. The present investigation showed that the antibacterial 3D printed filament can be used for the development of functional and effective antibacterial finger prostheses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".