Abstract
ChatGPT-3.5, an AI language model capable of text generation, translation, summarization, and question-answering, has recently been released for public use. Studies have shown it can ...generate abstracts, research papers, and dissertations, and create quality essays on different topics. This led to ethical issues in using ChatGPT in academic writing, AI authorship, and evaluating students’ essays. However, it is still unknown how ChatGPT performs in students’ environments as a writing assistant tool and if it enhances students’ essay-writing performance. In the present study, we examined students’ essay-writing performances with or without ChatGPT as an essay-writing assistance tool. The average essay grade was C for both control (traditional essay-writing,
n
= 9) and experimental (ChatGPT-assisted essay-writing,
n
= 9) groups. None of the predictors affected essay scores: group, writing duration, study module, and GPA. The text unauthenticity was slightly higher in the experimental group, but the similarity among essays was generally low in the overall sample. In the experimental group, the AI classifier recognized more potential AI-generated texts. Our results demonstrate that the ChatGPT group did not perform better in either of the indicators; the students did not deliver higher quality content, did not write faster, nor had a higher degree of authentic text. We anticipate that these results can relieve some concerns about this tool’s usage in academic writing. ChatGPT-assisted writing could depend on the previous knowledge and skills of the user, which might, in certain instances, lead to confusion in inexperienced users and result in poorer essay writing performance.
To examine seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in industry workers population sample.
From 23 to April 28, 2020, we conducted serological testing ...for antibodies (Immunoglobulin G (IgG) and Immunoglobulin M (IgM)) on 1494 factory employees living in the Split-Dalmatia and Šibenik-Knin County (Croatia).
We detected antibodies in 1.27% of participants (95% confidence interval CI 0.77-1.98%). In Split facility 13/1316 (0.99%, 95% CI 0.53-1.68%) of participants were tested positive, of which 13/1079 (1.20%, 95% CI 0.64-2.05%) of those living outside the facility and 0/237 (0%, 95% CI 0-1.26%) of those living inside the facility. In Knin facility, 6/178 (3.37%, 95% CI 1.25-7.19%) participants were tested positive for antibodies.
The study showed relatively small SARS-CoV-2 antibody seroprevalence in the DIV Group population sample.
The osteometric methods are the most reliable way to estimate the sex of skeletons when DNA analysis is not used. However, as osteometric studies usually ignore the overlap in male and female ...skeletal dimensions, they rarely achieve accuracy sufficient for forensic application. To resolve this issue, recent studies suggest sex estimation only when posterior probability (pp) is greater than 0.95, but that approach does not always provide sufficient accuracy and creates a large proportion of unsexed skeleton. Thus, our study aimed to explore whether it is possible to adjust pp on skeletal measurements with pronounced sexual dimorphism to meet 95% accuracy and to enable sex estimation on a reasonable proportion of individuals. From 207 skeletons, we included 65 postcranial measurements and selected 10% of variables with the highest sexual dimorphism. We computed univariate and bivariate discriminant functions using pp threshold of 0.5, 0.95, and the threshold required to achieve accuracy of ≥ 95%. Discriminant functions with pp=0.5 obtained accuracy of 85%–93%, while those with pp≥0.95 and adjusted posterior probabilities obtained 94%–99%. However, we showed that by selecting a particular threshold, sex could be estimated on a greater proportion of individuals than for pp≥0.95: 42%–86% vs. 24%–62% for univariate and 69%–95% vs. 49%–78% for bivariate functions. Therefore, when developing sex estimation models, we suggest not to use fixed pp level, but to adjust pp to achieve 95% accuracy and to minimize the percentage of unsexed skeletons.
•We developed a binary classification method for optimizing classification thresholds.•As example data, we used three male and female handprint measurements (n=160).•We tested classification ...performances of LDA by traditional and proposed approach.•Traditional approach provided accuracies 78.7–92.5 % and PPVs/NPVs 78.2–93 %.•The newly proposed approach provided accuracies ≥ 95 % and PPVs/NPVs ≥ 95 %.
Binary classification techniques are commonly used in forensic examination to test if a specimen belongs to a particular group and base the expert opinion on the questioned evidence. However, most of the currently used methods do not achieve sufficient accuracy due to the ignoring of the specimens classified in the overlapping area. To address the issue, we proposed a novel Adjusted binary classification (ABC) algorithm that automatically adjusts posterior probabilities to reach classification accuracy and positive/negative predicted values (PPV, NPV) of 95 %.
In the presented example, we used three handprint measurements from 160 participants (80 males and 80 females) to develop models that would classify sex from their dimensions. The sample was split into the training/cross-validated (70 %) and testing sample (30 %). We developed four classification models using linear discriminant analysis (LDA) by employing traditional single cut-off values and ABC approach that for each group provides a specific posterior probability cut-off threshold.
In the cross-validated sample, the accuracy of traditional models was 78.7–92.5 %, while PPVs/NPVs ranged between 78.2 and 93 %. ABC models provided 95 % accuracy, PPV, and NPV, and could classify 35.5–88.1 % of specimens. In the testing sample, ABC models achieved accuracy of 97.3–100 %, PPV/NPV 95.4–100 %, and could be applied to 29.1–87.5 % of specimens.
The study demonstrated that the ABC approach could adjust classification models to reach predefined values of accuracy, PPV, and NPV. Therefore, it could be an efficient tool for conducting a binary classification in forensic settings and minimizing the possibilities of incorrect classifications.
Coming out process is a necessary step for a LGBTQ person in order to develop integrative sexual and transgender identity (Cass, 1984; Manning, 2014). and mental health of LGBTQ people is under ...strong influence by the family and social support and their reactions to coming out (D'Augelli, 2002; Ryan et al., 2010; Ryan, Legate, & Winstein, 2015). The goal of the present research is to explore what is the experience of mothers of LGBTQ children in Serbia after the children's coming out? Using the Interpretative Phenomenological Analysis (Smith, 2015), this study explored the experience of eight mothers of LGBTQ youth in Serbia after their children came out. From the analysis 4 main themes emerged: We started a conversation, and then he told me everything: what, how, where" - The context of finding out, "...and that is something very terrifying, that someone could hurt my child because he is what he is" - Mothers' reactions, "I needed to see that he is completely well" - Process of adaptation, "Are we strong enough to bear all that?" - Parent and family identity. The results have shown that after finding out, mothers have a broad variety of reactions from surprise and shock to anger and sadness (Ben-Ari, 1989), after which the process of accepting child's identity begins. That process was composed of different questions and challenges mothers faced and needed to overcome, either with professional or support from co-parent, with social support and information gathered from children or internet. The adaptation process resulted in integration of child's identity in family's identity, showing a developmental path mothers go through in order to accept child's identity, but also showing possibilities for practical interventions in working with LGBTQ children and their families.
The study aimed to test the applicability of the Probabilistic Sex Diagnosis (DSP) method in the bioarchaeological context by validation with known sex data obtained by aDNA analysis on the medieval ...samples from the Eastern Adriatic coast. We tested the method on 57 skeletons of known sex using 30 different combinations of measurements. The possibility of sex estimation ranged from 35.90 to 86.11% depending on the combinations used while sexing accuracy ranged from 92.86 to 100%. Females were classified correctly in all cases, and only one male was misclassified in all combinations that could be tested. Accuracy rates higher than 95% were obtained for every combination where the number of available measurements was larger than 15. Therefore, we encourage further validation of the method on different ancient populations and implementation of the method for creating reference sex data and development of metric and non-metric population-specific sex estimation standards.
•We tested DSP method by comparison to known sex data obtained by aDNA analysis.•Sample consisted of 57 skeletons from medieval Eastern Adriatic coast sites.•Depending on chosen measurements sex could be estimated in 35.90–86.11% cases.•Sexing accuracy ranged from 92.86 to 100%.•We suggest DSP method for creating reference data for sex in ancient populations.
The adjusted binary classification (ABC) approach was proposed to assure that the binary classification model reaches a particular accuracy level. The present study evaluated the ABC for osteometric ...sex classification using multiple machine learning (ML) techniques: linear discriminant analysis (LDA), boosted generalized linear model (GLMB), support vector machine (SVM), and logistic regression (LR). We used 13 femoral measurements of 300 individuals from a modern Turkish population sample and split data into two sets: training (n = 240) and testing (n = 60). Then, the five best-performing measurements were selected for training univariate models, while pools of these variables were used for the multivariable models. ML classifier type did not affect the performance of unadjusted models. The accuracy of univariate models was 82−87%, while that of multivariate models was 89−90%. After applying ABC to the crossvalidation set, the accuracy and the positive and negative predictive values for uni- and multivariate models were ≥95%. Sex could be estimated for 28−75% of individuals using univariate models but with an obvious sexing bias, likely caused by different degrees of sexual dimorphism and between-group overlap. However, using multivariate models, we minimized the bias and properly classified 81−87% of individuals. A similar performance was also noted in the testing sample (except for FEB), with accuracies of 96−100%, and a proportion of classified individuals between 30% and 82% in univariate models, and between 90% and 91% in multivariate models. When considering different training sample sizes, we demonstrated that LR was the most sensitive with limited sample sizes (n < 150), while GLMB was the most stable classifier.
Reconstructing the face from the skull is important not only for forensic identification but also as a tool that can provide insight into the appearance of individuals from past populations. It ...requires a multidisciplinary approach that combines anthropological knowledge, advanced imaging methods, and artistic skills. In the present study, we demonstrate this process on the skull of an early medieval warrior from Croatia. The skeletal remains were prepared and scanned using multi-slice computed tomography (MSCT) and examined using standard anthropological and radiological methods. The analysis revealed that the remains belonged to a 35–45-year-old male individual who had suffered severe cranial trauma, probably causing his death. From MSCT images, we reconstructed a three-dimensional (3D) model of the skull, on which we digitally positioned cylinders demarking the soft tissue thickness and created the face with a realistic texture. A 3D model of the face was then optimized, printed, and used to produce a clay model. Sculpturing techniques added skin textures and facial features with scars and trauma manifestations. Finally, after constructing a plaster model, the model was painted and refined by adding fine details like eyes and hair, and it was prepared for presentation in the form of a sculpture.
Aim To determine the incidence of metopism in the modern and archaeological Croatian population. Methods A total of 800 specimens (454 modern multi-slice computed tomography MSCT scans and 346 dry ...archaeological skulls) were visually examined for metopic suture presence. The metopic suture was deemed complete when aligned nasion to bregma. Results In the overall sample, the metopic suture was observed in 36 of 800 subjects (4.5%): 19 of 424 (4.5%) men and 17 of 370 (4.6%) women. A significant difference was not observed between modern and archaeological samples (chi square = 3.219, P = 0.359) or between the sexes (chi square = 0.006, P = 0.939). The frequency of metopism varied from 3.5% in the modern population to 7.04% in the samples from the Roman period. Conclusion There are no visible secular changes on metopic suture in the Croatian population through time. Some variations can be the result of differences in sample size in different time periods.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract This study investigated the stroke and slope characteristics in left‐handed and right‐handed handwriting. Stroke (letters t, f, đ, and H) and slope (letters t, f, l, d, and g) directions ...were analyzed on in‐house samples ( n = 64), revealing statistically significant differences ( p ≤ 0.05) between the groups. Right‐handers predominantly exhibited left‐to‐right strokes (98%–100%), while left‐handers showed greater variability. Although statistically significant for most letters analyzed, slope direction did not demonstrate consistent patterns. A logistic regression model was developed and validated on the same sample to classify handedness based on the averaged strokes of the letter “t.” The model was further tested on samples ( n = 252) from a publicly available handwriting database. If the model classified the sample as produced by left hand, it was correct in 100% of cases. In contrast, when the model classified writing as right‐handed, it was correct in 73%–97% of cases, depending on the validation sample. The model classified writing as of left‐handed origin if more than 36% of the letters “t” had a stroke from right to left, while otherwise, writing was classified as of right‐handed origin. The developed method showed great potential for classifying the handedness of the author of disputed handwriting, thus eliminating individuals as text authors or narrowing down the pool of potential authors.
PDF
