Corrigendum to “Antimicrobial topical polymeric films loaded with Acetyl-11-keto-β-boswellic acid (AKBA), boswellic acid and silver nanoparticles: Optimization, characterization, and biological activity” [Heliyon 10(11) 15th June 2024, e31671]
Bibliographic record
Abstract
In the original published version of this article, the structure of CMC in figure 6 was incorrect, it was of cellulose, and the spelling of sodium alginate was wrong. The correct structure of CMC has now been added, and sodium alginate has been denoted as SA. The correct version can be found below. There were also some slight changes made to the text of section 3.11 to reflect the changes to figure 6. The authors/publisher apologize for the errors. Both the HTML and PDF versions of the article have been updated to correct the errors. DOI of original article: https://doi.org/10.1016/j.heliyon.2024.e31671 Marcus Bunduka: Conceptualization Antimicrobial topical polymeric films loaded with Acetyl-11-keto-β-boswellic acid (AKBA), boswellic acid and silver nanoparticles: Optimization, characterization, and biological activityJawad et al.HeliyonMay 24, 2024In BriefThe study examined the antimicrobial and antioxidant potential of pure Acetyl-11-keto-β-boswellic acid (AKBA), boswellic acid (70%) and AKBA loaded nanoparticles as topical polymeric films. The optimized concentration (0.05 % w/v) of pure AKBA, boswellic acid (BA), and AKBA loaded silver nanoparticles were used to study its impact on film characteristics. Carboxymethyl cellulose (CMC), sodium alginate (SA), and gelatin (Ge) composite films were prepared in this study. The polymeric films were evaluated for their biological (antioxidant and antimicrobial activities) and mechanical characteristics such as tensile strength (TS) and elongation (%). Full-Text PDF Open Access
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.147 | 0.089 |
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".