Suchergebnisse - (( (stat OR (stateen OR stateeee)) python code analysis ) OR ( statement 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

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

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

Programmed differently? Testing for gender differences in Python programming style and quality on GitHub.

Autoren: Brooke, Siân

Quelle: Journal of Computer-Mediated Communication; Jan2024, Vol. 29 Issue 1, p1-13, 13p

Schlagwörter: PYTHON programming language, PYTHONS, RANDOM forest algorithms, GENDER

Entropy, Fidelity, and Entanglement During Digitized Adiabatic Quantum Computing to Form a Greenberger–Horne–Zeilinger (GHZ) State.

Autoren: Jansen, Nathan D. Hunt, Katharine L. C.

Quelle: Entropy; Sep2025, Vol. 27 Issue 9, p891, 21p

Schlagwörter: ENTROPY, QUANTUM entanglement, STATISTICAL accuracy, HAMILTONIAN mechanics, ISING model, QUANTUM computing, QUANTUM computers

Firma/Körperschaft: INTERNATIONAL Business Machines Corp.

An extensive study of the effects of different deep learning models on code vulnerability detection in Python code.

Autoren: Wang, Rongcun Xu, Senlei Ji, Xingyu et al.

Quelle: Automated Software Engineering; Jun2024, Vol. 31 Issue 1, p1-35, 35p

A FASTER MULTIPOLE LEGENDRE-CHEBYSHEV TRANSFORM.

Autoren: MORTENSEN, MIKAEL

Quelle: SIAM Journal on Scientific Computing; 2024, Vol. 46 Issue 6, pA3803-A3826, 24p

Schlagwörter: FAST multipole method, MACBOOK Pro, DISCRETE cosine transforms, ALGORITHMS, PYTHON programming language

Unsupervised Voting for Detecting the Algorithmic Solving Strategy in Competitive Programming Solutions.

Autoren: Stoica, Alexandru Stefan Babiceanu, Daniel Mihaescu, Marian Cristian et al.

Quelle: Mathematics (2227-7390); Nov2025, Vol. 13 Issue 22, p3589, 19p

Schlagwörter: MACHINE learning, CLUSTERING algorithms, COMPUTER science, ALGORITHMS, SOURCE code

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.

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.

Evolution of technical debt remediation in Python: A case study on the Apache Software Ecosystem.

Autoren: Tan, Jie Feitosa, Daniel Avgeriou, Paris et al.

Quelle: Journal of Software: Evolution & Process; Apr2021, Vol. 33 Issue 4, p1-25, 25p

Schlagwörter: SHORT-term debt, PYTHON programming language, DEBT, PROGRAMMING languages, COMPUTER software

An Improved Copula‐Based Framework for Efficient Global Sensitivity Analysis.

Autoren: Liu, Hongli Clark, Martyn P. Gharari, Shervan et al.

Quelle: Water Resources Research; Jan2024, Vol. 60 Issue 1, p1-22, 22p

Schlagwörter: SENSITIVITY analysis, GAUSSIAN mixture models, DATA envelopment analysis, PARAMETER estimation

SparseCoder: Advancing source code analysis with sparse attention and learned token pruning.

Autoren: Yang, Xueqi Jakubowski, Mariusz Kang, Li et al.

Quelle: Empirical Software Engineering; Feb2025, Vol. 30 Issue 1, p1-30, 30p

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.

Survival Modelling Using Machine Learning and Immune–Nutritional Profiles in Advanced Gastric Cancer on Home Parenteral Nutrition.

Autoren: Matysiak, Konrad Hojdis, Aleksandra Szewczuk, Magdalena

Quelle: Nutrients. Aug2025, Vol. 17 Issue 15, p2414. 16p.

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.

Anti-Inflammatory Diet and Probiotic Supplementation as Strategies to Modulate Immune Dysregulation in Autism Spectrum Disorder.

Autoren: Naranjo-Galvis, Carlos Andrés Trejos-Gallego, Diana María Correa-Salazar, Cristina et al.

Quelle: Nutrients. Aug2025, Vol. 17 Issue 16, p2664. 21p.

Extended sample size calculations for evaluation of prediction models using a threshold for classification.

Autoren: Whittle, Rebecca Ensor, Joie Archer, Lucinda et al.

Quelle: BMC Medical Research Methodology; 7/1/2025, Vol. 25 Issue 1, p1-12, 12p

Schlagwörter: SAMPLE size (Statistics), PREDICTION models, RESEARCH personnel, MODEL validation, CALIBRATION

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

Sweet Taste Adaptation to Sugars, Sucralose, and Their Blends: A Human and Rodent Perspective.

Autoren: Okoye, Stephanie I. Kim, Minjae Petty, Sara et al.

Quelle: Nutrients. Oct2025, Vol. 17 Issue 19, p3075. 16p.