Search Results - (( (statu OR stat) python code analysis ) OR ( (stateen OR stavebnit) python code analysis ))*

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

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

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

Subject Terms: 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.

Authors: Dunker, Fabian Mendoza, Emil Reale, Marco

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

Subject Terms: 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.

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

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

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

Testing an Educational Program to Improve Goals of Care Conversations Between Patients and Their Care Teams

Authors: National Cancer Institute (NCI)

Source: A Randomized Controlled Trial of an Intervention Called "Algorithm-Enabled Patients Activated in Cancer Care Through Teams" (A-PACT) to Improve Goals of Care Communication for People With Cancer

An Empirical Evaluation of Ensemble Models for Python Code Smell Detection.

Authors: Rao, Rajwant Singh Dewangan, Seema Mishra, Alok

Source: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7472, 27p

Subject Terms: ENSEMBLE learning, FEATURE selection, BOOSTING algorithms, PYTHON programming language, COMPUTER software quality control, DESIGN failures, DATA augmentation

Recurrence Quantification Analysis Based Methodology in Automatic Aerobic Threshold Detection: Applicability and Accuracy across Age Groups, Exercise Protocols and Health Conditions

Authors: Serantoni C. De Spirito M. Maulucci G. et al.

Contributors: Serantoni C. De Spirito M. Maulucci G. et al.

Subject Terms: aerobic transition, athletes, cardiac signal processing, cardiorespiratory monitoring, heart rate variability, nonlinear time series analysis, obesity, python code, wearable and portable sensors, Settore PHYS-06/A - Fisica per le scienze della vita, l'ambiente e i beni culturali

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001342706200001; volume:14; issue:20; firstpage:N/A; lastpage:N/A; issueyear:2024; journal:APPLIED SCIENCES; https://hdl.handle.net/10807/311687

Availability: https://hdl.handle.net/10807/311687
https://doi.org/10.3390/app14209216

Primary data for BJC Carbonic anhydrase IX is a pH-stat that sets an acidic tumour extracellular pH in vivo

Authors: Griffiths, JR Lee, Shen-Han McIntyre, Dominick John et al.

Index Terms: Carbonic anhydrase IX, Extracellular pH, Intracellular pH, ISUCA, Magnetic Resonance Spectroscopy, MRS, pH-stat, Tumour pH, Dataset

URL: https://www.repository.cam.ac.uk/handle/1810/361916
https://doi.org/10.17863/CAM.26029
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141
https://doi.org/10.1038/s41416-018-0216-5
https://www.repository.cam.ac.uk/handle/1810/287141

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

Authors: Brooke, Siân

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

Subject Terms: PYTHON programming language, PYTHONS, RANDOM forest algorithms, GENDER

Towards the genome-scale discovery of bivariate monotonic classifiers.

Authors: Fourquet, Océane Krejca, Martin S. Doerr, Carola et al.

Source: BMC Bioinformatics; 9/2/2025, Vol. 26 Issue 1, p1-32, 32p

Subject Terms: CLASSIFICATION, BIOMARKERS, ALGORITHMS, MACHINE learning, BIOINFORMATICS

Insights and Analysis of Open-source License Violation Risks in LLMs Generated Code.

Authors: Yibo Wang Ying Wang Yue Yu et al.

Source: International Journal of Software & Informatics; 2025, Vol. 15 Issue 2, p145-173, 29p

Subject Terms: OPEN source software, COPYRIGHT infringement, LANGUAGE models, DATA analytics, CODE generators, INTELLECTUAL property infringement, DETECTION algorithms

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

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

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

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

Company/Entity: INTERNATIONAL Business Machines Corp.

Uncertainty quantification for severe-accident reactor modelling: Results and conclusions of the MUSA reactor applications work package

Authors: Brumm, S. Gabrielli, F. Sanchez Espinoza, V. et al.

Contributors: Brumm, S. Gabrielli, F. Sanchez Espinoza, V. et al.

Source: ISSN: 0306-4549 ; Annals of Nuclear Energy ; https://hal.science/hal-04777159 ; Annals of Nuclear Energy, 2025, 211, pp.110962. ⟨10.1016/j.anucene.2024.110962⟩.

Subject Terms: Nuclear reactor, Severe accident, Modelling, Uncertainty quantification, MUSA, Source Term, [PHYS]Physics [physics], [SPI]Engineering Sciences [physics], [STAT]Statistics [stat]

Relation: info:eu-repo/grantAgreement//847441/EU/Euratom research and training programme 2014 – 2018/Euratom

Availability: https://hal.science/hal-04777159
https://hal.science/hal-04777159v1/document
https://hal.science/hal-04777159v1/file/Final_version_ANE20225.pdf
https://doi.org/10.1016/j.anucene.2024.110962

HABiC: an algorithm based on the exact computation of the Kantorovich-Rubinstein optimizer for binary classification in transcriptomics.

Authors: Cordier, Chiara Jézéquel, Pascal Campone, Mario et al.

Source: Bioinformatics; Jun2025, Vol. 41 Issue 6, p1-13, 13p

Subject Terms: PREDICTION algorithms, TRANSCRIPTOMES, DEGREES of freedom, INDIVIDUALIZED medicine, MACHINE learning

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

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

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

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

Reviewing seas of data: Integrating image‐based bio‐logging and artificial intelligence to enhance marine conservation.

Authors: Chimienti, Marianna Kato, Akiko Seydi, Vahid et al.

Source: Methods in Ecology & Evolution; Feb2026, Vol. 17 Issue 2, p272-290, 19p

Subject Terms: ARTIFICIAL intelligence, COMPUTER vision, ANIMAL tagging, ENVIRONMENTAL sciences, COOPERATION, IMAGE processing, MARINE resources conservation, DATA integration

CQLLM: A Framework for Generating CodeQL Security Vulnerability Detection Code Based on Large Language Model.

Authors: Wang, Le Chen, Chan Zhu, Junyi et al.

Source: Applied Sciences (2076-3417); Jan2026, Vol. 16 Issue 1, p517, 17p

Subject Terms: COMPUTER security vulnerabilities, LANGUAGE models, COMPUTER software correctness, SOFTWARE frameworks, PENETRATION testing (Computer security), CODE generators

ΔCORONA-COUPLAGE-TEST v1.0 — Empirical Validation of Mimetic Magnetic Coherence in the Solar Corona

Authors: Tabary, Frédéric Zoran🦋Adapti

Subject Terms: Wavelet Coherence Analysis, Magnetohydrodynamics (MHD), Zoran🦋Adapti, Solar Physics, AI for Science, EthicChain / C2PA ProofChain, Reproducible Research, Zoran Mimetic Framework (GHUC Ω⁵), Coronal Heating Problem, Alfvén Waves, Mutual Information, IA chercheuse, Magnetic Coherence, Mimetic Coupling, zoran🦋aSiM, IA mimetique, zoran IA Mimetic, Energy–Information Coupling, Couronne Solaire, Information Physics, Self-Organization

GE-IA-NAM: gene–environment interaction analysis via imaging-assisted neural additive model.

Authors: Li, Jingmao Xu, Yaqing Ma, Shuangge et al.

Source: Bioinformatics; Sep2025, Vol. 41 Issue 9, p1-9, 9p

Subject Terms: CANCER research, GENOTYPE-environment interaction, DIAGNOSTIC imaging, DEEP learning, EMPIRICAL research, COMPUTER simulation

Gistable: Evaluating the Executability of Python Code Snippets on GitHub

Authors: Horton, Eric Parnin, Chris

Source: 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME). :217-227

Subject Terms: Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Software Engineering, 8. Economic growth, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: http://arxiv.org/pdf/1808.04919
http://arxiv.org/abs/1808.04919

Distinguishing LLM-Generated from Human-Written Code by Contrastive Learning.

Authors: Xu, Xiaodan Ni, Chao Guo, Xinrong et al.

Source: ACM Transactions on Software Engineering & Methodology; May2025, Vol. 34 Issue 4, p1-31, 31p

Subject Terms: CHATGPT, LANGUAGE models, CODE generators, MACHINE learning