'Doing good science is hard': retraction of high-profile reproducibility study prompts soul-searching
The retraction of a prominent reproducibility study reveals significant challenges in scientific research integrity and the effectiveness of preregistration.
Eureka! How a Stanford study revealed the success of research failures
The importance of acknowledging negative results for building a stronger scientific foundation and restoring public trust.
Emphasis on experimental rigor and the impact of flawed research designs leading to inaccurate conclusions.
'Doing good science is hard': retraction of high-profile reproducibility study prompts soul-searching
The retraction of a prominent reproducibility study reveals significant challenges in scientific research integrity and the effectiveness of preregistration.
Eureka! How a Stanford study revealed the success of research failures
The importance of acknowledging negative results for building a stronger scientific foundation and restoring public trust.
Emphasis on experimental rigor and the impact of flawed research designs leading to inaccurate conclusions.
Using AI in science can add to reproducibility woes
AI in science can hinder reproducibility due to lack of documentation and understanding of AI tools, leading to concerns about the robustness of AI-based discoveries.
Cash for catching scientific errors
Science needs enhanced error detection methods to improve reliability.
The ERROR project aims to systematically identify and correct research mistakes.
Using AI in science can add to reproducibility woes
AI in science can hinder reproducibility due to lack of documentation and understanding of AI tools, leading to concerns about the robustness of AI-based discoveries.
Cash for catching scientific errors
Science needs enhanced error detection methods to improve reliability.
The ERROR project aims to systematically identify and correct research mistakes.
Plagiarism involving text from LLMs is prohibited, except for experimental analysis. AI systems like ChatGPT cannot be used as citable sources. Allegations will be rigorously investigated.
Large Language Models for Code: Exploring the Landscape, Opportunities, and Challenges
GitHub Copilot introduced a breakthrough in large language models for code, improving engineer productivity by reducing code iterations.
Apple Open-Sources One Billion Parameter Language Model OpenELM
OpenELM, Apple's Transformer-based language model, uses scaled-attention mechanism, outperforms similar models with fewer tokens, and is reproducible by anyone.
Reusable research Birds of a Feather session at Scipy 2023: Solutions and tools
Notebooks should not be considered a unit of reproducible research, complete software projects are more suitable.
Tools like Papermill and Devcontainers can aid in parameterizing and executing notebooks programmatically.