Negative equity - the value of reporting negative results.

IF 4 3区 医学 Q2 CELL BIOLOGY
Disease Models & Mechanisms Pub Date : 2024-08-01 Epub Date: 2024-08-30 DOI:10.1242/dmm.050937
Owen Sansom, Debora Bogani, Linus Reichenbach, Sara Wells
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引用次数: 0

Abstract

A pervasive discussion point within the scientific community is the value of unpublished or unavailable data. Researchers, funders, ethical review bodies, editors and publishers have all highlighted the need to make more data available to enhance experimental planning and interpretation and to prevent others from repeating similar experiments. This is particularly important in the context of experimentation involving animals and efforts towards replacement, refinement and reduction. However, despite this broad agreement, sharing data that show inconclusive, statistically insignificant or unremarkable results is still not common practice. In this Editorial, we will highlight the value of what are often coined negative (or null) data and outline some emerging initiatives to address the gap between data generated in laboratories and data available to the wider scientific community.

负资产--报告负面结果的价值。
科学界普遍讨论的一个问题是未发表或不可用数据的价值。研究人员、资助者、伦理审查机构、编辑和出版商都强调需要提供更多数据,以加强实验规划和解释,并防止他人重复类似实验。这一点对于涉及动物的实验以及替代、改进和减少实验的努力尤为重要。然而,尽管存在这种广泛的共识,但共享那些显示不确定、统计上不重要或不显著结果的数据仍不是普遍做法。在这篇社论中,我们将强调通常被称为阴性(或空)数据的价值,并概述一些新出现的倡议,以解决实验室产生的数据与更广泛的科学界可获得的数据之间的差距。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Disease Models & Mechanisms
Disease Models & Mechanisms 医学-病理学
CiteScore
6.60
自引率
7.00%
发文量
203
审稿时长
6-12 weeks
期刊介绍: Disease Models & Mechanisms (DMM) is an online Open Access journal focusing on the use of model systems to better understand, diagnose and treat human disease.
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