Automated Author ProfileLucena, Luciana Vaz de Oliveira
Lucena, Luciana Vaz de Oliveira
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
ABSTRACT Purpose: to analyze the criteria most used by experts in the handwriting analysis report. Methods: a descriptive, quantitative, inferential, and cross-sectional study, with statistical analysis of the results obtained with a form administered to the experts. The statistical calculations were made with R language, version 4.0.1, with statistical significance set at 5%. Results: the absolute frequency analysis indicated a greater occurrence of the use of initial and final pen strokes and handwriting progress, with a relative frequency above 70%. A detailed evaluation with univariate analysis showed that these criteria are not relevant to correct conclusions in the expert analysis report. It also pointed out that morphology is a relevant criterion to infer whether an evaluation is correct. The data showed that initial pen stroke, inclination, dynamism, and evolution, when observed in terms of multivariate modeling, were not significant, indicating that subjectivity is essential for the experts to make correct analyses. Conclusion: the most reported expert handwriting analysis criteria in relation to the experts’ correct analyses were not statistically relevant for the development of the analysis reports.
Authors
- Melo, Ana Patrícia Carvalho de ;
- Bezerra, Byron Leite Dantas ;
- Lopes Júnior, Celso Antônio Marcionilo ;
- Lima, Fernanda Gabrielle Andrade ;
- Lucena, Luciana Vaz de Oliveira ;
- Stodolni, Murilo Campanhol ;
- Meneses, Denise Costa ;
- Advíncula, Karina Paes
ABSTRACT Purpose: to analyze the criteria most used by experts in the handwriting analysis report. Methods: a descriptive, quantitative, inferential, and cross-sectional study, with statistical analysis of the results obtained with a form administered to the experts. The statistical calculations were made with R language, version 4.0.1, with statistical significance set at 5%. Results: the absolute frequency analysis indicated a greater occurrence of the use of initial and final pen strokes and handwriting progress, with a relative frequency above 70%. A detailed evaluation with univariate analysis showed that these criteria are not relevant to correct conclusions in the expert analysis report. It also pointed out that morphology is a relevant criterion to infer whether an evaluation is correct. The data showed that initial pen stroke, inclination, dynamism, and evolution, when observed in terms of multivariate modeling, were not significant, indicating that subjectivity is essential for the experts to make correct analyses. Conclusion: the most reported expert handwriting analysis criteria in relation to the experts’ correct analyses were not statistically relevant for the development of the analysis reports.
Authors
- Melo, Ana Patrícia Carvalho de ;
- Bezerra, Byron Leite Dantas ;
- Lopes Júnior, Celso Antônio Marcionilo ;
- Lima, Fernanda Gabrielle Andrade ;
- Lucena, Luciana Vaz de Oliveira ;
- Stodolni, Murilo Campanhol ;
- Meneses, Denise Costa ;
- Advíncula, Karina Paes