Suchergebnisse - (( (stat OR (statement OR stateeement)) python code analysis ) OR ( statni python code analysis ))~

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

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.

Sub-grouping Kho-Bwa based on shared core vocabulary

Autoren: Lieberherr, Ismael Bodt, Timotheus Adrianus

Quelle: Himalayan Linguistics. 16(2)

Schlagwörter: Historical Linguistics, Lexico-statistics, Tibeto-Burman, Kho-Bwa, Duhumbi, Sartang, Sherdukpen, Bugun, Puroik, Arunachal Pradesh, Python, Cluster Analysis

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/4t27h5fg
https://escholarship.org/content/qt4t27h5fg/qt4t27h5fg.pdf

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.

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.

Leveraging Static Analysis for Feedback-Driven Security Patching in LLM-Generated Code.

Autoren: Alrashedy, Kamel Aljasser, Abdullah Tambwekar, Pradyumna et al.

Quelle: Journal of Cybersecurity & Privacy; Dec2025, Vol. 5 Issue 4, p110, 29p

Schlagwörter: COMPUTER security vulnerabilities, LANGUAGE models, PROGRAM transformation, BENCHMARK problems (Computer science), SOFTWARE maintenance, SOURCE code

Enhanced cattle identification using Siamese network and MobileViT with EMA attention.

Autoren: Han, Mingshuo Li, Baoshan Li, Qi et al.

Quelle: Frontiers in Veterinary Science. 2026, p1-15. 15p.

A Systematic Survey on Large Language Models for Code Generation.

Autoren: Jabrw, Sardar K. Sarhan, Qusay I.

Quelle: ARO: The Scientific Journal of Koya University; 2025, Vol. 13 Issue 2, p83-99, 17p

Schlagwörter: LANGUAGE models, CODE generators, PROGRAMMING languages, EVALUATION research, COMPUTER software development, COMPUTER security vulnerabilities, NATURAL language processing

Sex-Specific Dietary Predictors of Blood Glucose Identified Through Decision Tree Modeling in Adults.

Autoren: Gautney, Joanna Aguilar, Christina Chan, Julian et al.

Quelle: Nutrients. Oct2025, Vol. 17 Issue 19, p3119. 12p.