Suchergebnisse - (( (statement OR stat) python code analysis ) OR ( (stateline OR stateeed) python code analysis ))~

Code Redteaming: Probing Ethical Sensitivity of LLMs Through Natural Language Embedded in Code.

Autoren: Park, Chanjun Yoon, Jeongho Lim, Heuiseok

Quelle: Mathematics (2227-7390). Jan2026, Vol. 14 Issue 1, p189. 18p.

Schlagwörter: *LANGUAGE models, *ETHICS, *NATURAL language processing, *RISK assessment, *MORAL attitudes

Bactogram: Spatial Analysis of Bacterial Colonization in Epidermal Wounds

Autoren: Wallblom, Karl Forsberg, Fredrik Lundgren, Sigrid et al.

Weitere Verfasser: Wallblom, Karl Forsberg, Fredrik Lundgren, Sigrid et al.

Schlagwörter: Medical and Health Sciences, Clinical Medicine, Dermatology and Venereal Diseases, Medicin och hälsovetenskap, Klinisk medicin, Dermatologi och venereologi

Zugangs-URL: https://doi.org/10.1101/2024.04.18.24305961

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autoren: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

Quelle: Future Internet; Sep2025, Vol. 17 Issue 9, p412, 28p

Schlagwörter: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

CLM App: Interlamellar Distance of Pearlite via CLM Revisited and Automated.

Autoren: Zouhar, Martin Mikmeková, Šárka Hovjacký, Jan et al.

Quelle: Materials (1996-1944); Feb2026, Vol. 19 Issue 3, p635, 17p

Schlagwörter: AUTOMATION, IMAGE analysis, QUALITY control, MICROSTRUCTURE

Economic and Veterinary Evaluation of Pet Insurance in Türkiye: Potential, Role in Health, and Impact on Practice.

Autoren: GENÇGÖNÜL, Betül Zehra¹ betul.zehra@hacettepe.edu.tr

Quelle: Kafkas Üniversitesi Veteriner Fakültesi Dergisi. Jan/Feb2026, Vol. 32 Issue 1, p147-153. 7p.

Textual Financial Data Repository and Python Code for Machine Learning, AI, and Textual Analyses: Major Sections from 10-K, 10-Q, and Financial Statement Notes

Autoren: Mauricio Codesso Rani Hoitash Udi Hoitash

Comparative Analysis of AI Models for Python Code Generation: A HumanEval Benchmark Study.

Autoren: Bayram, Ali Menekse Dalveren, Gonca Gokce Derawi, Mohammad

Quelle: Applied Sciences (2076-3417); Sep2025, Vol. 15 Issue 18, p9907, 17p

Schlagwörter: ARTIFICIAL intelligence, PYTHON programming language, COMPARATIVE studies, EVALUATION methodology, BENCHMARK problems (Computer science), GENERATIVE pre-trained transformers, MACHINE learning, COMPUTER software development

The state of the late Quaternary megafauna extinction debate: a systematic review and analysis.

Autoren: Stewart, Mathew Peters, Carli Ziegler, Michael J. et al.

Quelle: Frontiers in Mammal Science. 2025, p1-27. 27p.

Eating Disorders in People Who Identify as Gender-Diverse: Associations Between Gender Diversity, Eating Disorder Diagnosis, Minority Stress Experiences and Mental Health Comorbidity.

Autoren: Murphy, Rebecca Sharpe, Helen

Quelle: Nutrients. Feb2026, Vol. 18 Issue 3, p458. 24p.

Portable Electronic Olfactometer for Non-Invasive Screening of Canine Ehrlichiosis: A Proof-of-Concept Study Using Machine Learning.

Autoren: Durán Cotrina, Silvana Valentina Acevedo, Cristhian Manuel Durán Carrillo Gómez, Jeniffer Katerine

Quelle: Veterinary Sciences. Jan2026, Vol. 13 Issue 1, p88. 20p.

A statistical approach to automated analysis of the low‐contrast object detectability test for the large ACR MRI phantom.

Autoren: Golestani, Ali M. Gee, Julia M.

Quelle: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-9, 9p

Schlagwörter: LINEAR statistical models, IMAGING phantoms, QUALITY control, PYTHON programming language, MAGNETIC resonance imaging

Regularized Maximum Likelihood Estimation for the Random Coefficients Model in Python.

Autoren: Dunker, Fabian Mendoza, Emil Reale, Marco

Quelle: Mathematics (2227-7390); Dec2025, Vol. 13 Issue 23, p3764, 29p

Schlagwörter: PYTHON programming language, MAXIMUM likelihood statistics, CONSUMPTION (Economics), MATHEMATICAL programming, MULTILEVEL models, SCIENTIFIC computing

Varietal Differences in Kidney Beans Modulate Gut Microbiota and Inflammation During High-Fat Diet-Induced Obesity in Male Mice.

Autoren: Rodrigue, Alexane F. Pereira, Bruna B. Freije, Giorgio et al.

Quelle: Nutrients. Feb2026, Vol. 18 Issue 3, p461. 34p.

Zinc as a Biomarker of Nutritional Status and Clinical Burden in Recessive Dystrophic Epidermolysis Bullosa: Implications for Preventive Monitoring.

Autoren: Quintana-Castanedo, Lucía Maseda, Rocío Sánchez-Ramón, Silvia et al.

Quelle: Nutrients. Jan2026, Vol. 18 Issue 2, p232. 19p.

PreNNsem: A Heterogeneous Ensemble Learning Framework for Vulnerability Detection in Software.

Autoren: Wang, Lu Li, Xin Wang, Ruiheng et al.

Quelle: Applied Sciences (2076-3417); 11/15/2020, Vol. 10 Issue 22, p7954, 17p

Schlagwörter: DEEP learning, INTEREST rates, SOURCE code, COMPUTER software, VECTOR data

Strong correlation of gene counts and differentially expressed genes between a 3′ RNA-Seq and an RNA hybridization platform in transcriptome analyses from canine archival tissues.

Autoren: Haake, Alexander F. H. Loriani Fard, Alina K. Jovanovic, Vladimir M. et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Integrating multi-modal data fusion approaches for analysis of dairy cattle vocalizations.

Autoren: Jobarteh, Bubacarr Mincu-Iorga, Madalina Gavojdian, Dinu et al.

Quelle: Frontiers in Veterinary Science. 2025, p1-13. 13p.

Genome-wide analyses reveal intricate genetic mechanisms underlying egg production efficiency in chickens.

Autoren: Tan, Lizhi Cai, Xinyu Kong, Yuan et al.

Quelle: Journal of Animal Science & Biotechnology. 8/11/2025, Vol. 16 Issue 1, p1-21. 21p.

Orthorexia Profiles in Athletes: A Multidimensional Analysis Using the Eating Habits Questionnaire (EHQ) and the Teruel Orthorexia Scale (TOS).

Autoren: Manzanares-Cabrera, María Onieva-Zafra, María Dolores Bermejo-Cantarero, Alberto et al.

Quelle: Nutrients. Dec2025, Vol. 17 Issue 24, p3814. 17p.

Data-Driven Early Warning Approach for Antimicrobial Resistance Prediction–Anomaly Detection Based on High-Level Indicators.

Autoren: Csorba, Szilveszter Vribék, Krisztián Farkas, Máté et al.

Quelle: Veterinary Sciences. Oct2025, Vol. 12 Issue 10, p935. 17p.