Author

E. O. Buzbas

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Scientific Communication & Education· 3 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2

Frequent Co-Authors

B. Devezer· 3 shared B. Baumgaertner· 1 shared D. J. Navarro· 1 shared J. Vandekerckhove· 1 shared M. Lukaszewicz· 1 shared O. Issaka Salia· 1 shared P. A. Hohenlohe· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 7 mutual co-author links

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3 shared papersScientific Communication & Education

B. Devezer

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4 papers

Recent·Most cited

Approximate Bayesian computational methods to estimate the strength of divergent selection in population genomics models

M. Lukaszewicz, O. Issaka Salia, P. A. Hohenlohe, E. O. Buzbas

This study evaluates ABC methods for estimating divergent selection parameters using simulations and assesses summary statistics for their effectiveness.

bioRxiv · Jun 6, 2023Evolutionary Biology

Bridging the gap between formal theory and scientific reform practices

E. O. Buzbas, B. Devezer

The paper discusses the challenges of bridging theoretical knowledge and practical advancements in scientific reform, focusing on reproducibility and multi-lab replication studies.

bioRxiv · Dec 7, 2022Scientific Communication & Education

The logical structure of experiments lays the foundation for a theory of reproducibility

E. O. Buzbas, B. Devezer, B. Baumgaertner

This paper develops a theory of reproducibility by analyzing the logical structure of experiments and defining idealized experiments to clarify replication and results reproducibility.

bioRxiv · Aug 10, 2022 · PreprintScientific Communication & Education

The case for formal methodology in scientific reform

B. Devezer, D. J. Navarro, J. Vandekerckhove, E. O. Buzbas

The paper argues for formal statistical rigor in methodological reform and presents a formal analysis of three common metascientific claims.

bioRxiv · Apr 26, 2020Scientific Communication & Education