内容来源：OpenScience

预测论文可重复性 & 70个团队如何实锤fMRI分析的灵活性

OpenTalks是OpenScience正在尝试的一个新系列。在OpenTalks里，我们将邀请研究者进行在学术报告，学术报告的主题将与可重复性和开放科学相关，报告语言以中文为主，也可能邀请国际同行进行报告，届时将使用英文。欢迎大家推荐报告人或者自荐作为报告人。

本周六我们将在线进行两场学术报告，均是近期发表在知名期刊上学术论文的研究者。两场讲座均将采用中文进行报告。由于报告人分布在三大洲，因此在时间上我们不得进行妥协，对于在国内的小伙伴来说，时间可能有些晚。希望大家白天休息好，为晚上的学术盛宴作好准备！

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第一场

报告时间：北京时间5月23日22:00 ~ 22:50

Zoom信息：980 6252 1513

报告人：吴又又 (Northwestern University Institute on Complex Systems & Kellogg School of Management, Northwestern University)

报告题目：Estimating the deep replicability of scientific findings using human and artificial intelligence

摘要
Here, we trained an artificial intelligence model to estimate a paper’s replicability using ground truth data on studies that had passed or failed manual replication tests, and then tested the model’s generalizability on an extensive set of out-of-sample studies. The model predicts replicability better than the base rate of reviewers and comparably as well as prediction markets, the best present-day method for predicting replicability. In out-of-sample tests on manually replicated papers from diverse disciplines and methods, the model had strong accuracy levels of 0.65 to 0.78. Exploring the reasons behind the model’s predictions, we found no evidence for bias based on topics, journals, disciplines, base rates of failure, persuasion words, or novelty words like “remarkable” or “unexpected.” We did find that the model’s accuracy is higher when trained on a paper’s text rather than its reported statistics and that n-grams, higher order word combinations that humans have difficulty processing, correlate with replication.

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第二场

报告时间：北京时间5月23日22:55 ~ 23:45

Zoom信息：980 6252 1513

报告人：邸新博士、胡传鹏博士、孔祥祯博士、沈强博士、苑瑞博士、张磊博士

报告题目：Variability in the analysis of a single neuroimaging dataset by many teams

讨论嘉宾：王鑫迪博士等

组织团队：

NeuroChat

OpenScience