Drawing on our experiences conducting replications we describe the lessons we learned about replication studies and formulate recommendations for researchers, policy makers, and funders about the role of replication in science and how it should be supported and funded. We first identify a variety of benefits of doing replication studies. Next, we argue that it is often necessary to improve aspects of the original study, even if that means deviating from the original protocol. Thirdly, we argue that replication studies highlight the importance of and need for more transparency of the research process, but also make clear how difficult that is. Fourthly, we underline that it is worth trying out replication in the humanities. We finish by formulating recommendations regarding reproduction and replication research, aimed specifically at funders, editors and publishers, and universities and other research institutes.
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http://dx.doi.org/10.1080/08989621.2024.2383349 | DOI Listing |
Oper Neurosurg (Hagerstown)
July 2024
Neurosurgical Simulation and Artificial Intelligence Learning Centre, Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal , Quebec , Canada.
Background And Objectives: Subpial corticectomy involving complete lesion resection while preserving pial membranes and avoiding injury to adjacent normal tissues is an essential bimanual task necessary for neurosurgical trainees to master. We sought to develop an ex vivo calf brain corticectomy simulation model with continuous assessment of surgical instrument movement during the simulation. A case series study of skilled participants was performed to assess face and content validity to gain insights into the utility of this training platform, along with determining if skilled and less skilled participants had statistical differences in validity assessment.
View Article and Find Full Text PDFAtten Percept Psychophys
January 2025
Department of Psychology, Huron University College at Western: London, 1349 Western Road, London, ON, N6G 1H3, Canada.
Previous studies have reported visual motion aftereffects (MAEs) following prolonged exposure to auditory stimuli depicting motion, such as ascending or descending musical scales. The role of attention in modulating these cross-modal MAEs, however, remains unclear. The present study manipulated the level of attention directed to musical scales depicting motion and assessed subsequent changes in MAE strength.
View Article and Find Full Text PDFTrop Anim Health Prod
January 2025
Animal Science Department, Federal University of Paraná, Palotina, PR, 85950-000, Brazil.
This study aimed to evaluate the effect of autolyzed yeast (obtained from culture of Saccharomyces cerevisiae in sugarcane derivatives) supplementation on diet digestibility, feeding behavior, levels of blood metabolites associated with protein and energy metabolism, and performance of Dorper × Santa Ines lambs finished in feedlot. Twenty-four non-castrated male lambs with an average age of 4 months and a body weight (BW) of 19.49 ± 3.
View Article and Find Full Text PDFArch Microbiol
January 2025
Department of Biological Sciences, Birla Institute of Technology and Science, Pilani, K K Birla Goa Campus, NH17B, Zuarinagar, Goa, 403726, India.
The gene gp13 in bacteriophage Phi11 has been annotated as a Single-Stranded DNA binding protein (SSB protein, GenBank accession no. NC_004615.1).
View Article and Find Full Text PDFEur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
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