How journals are fighting back against a wave of questionable images
期刊如何反击一波有问题的图像
Journals are making an effort to detect manipulated images of the gels used to analyse proteins and DNA.Credit: Shutterstock
期刊正在努力检测用于分析蛋白质和DNA的凝胶的操纵图像。
It seems that every month brings a fresh slew of high-profile allegations against researchers whose papers — some of them years old — contain signs of possible image manipulation.
似乎每个月都会有一系列针对研究人员的高调指控，这些研究人员的论文-其中一些已经有好几年了-包含可能的图像操纵迹象。
Scientist sleuths are using their own trained eyes, along with commercial software based on artificial intelligence (AI), to spot image duplication and other issues that might hint at sloppy record-keeping or worse. They are bringing these concerns to light in places like PubPeer, an online forum featuring many new posts every day flagging image concerns.
科学家侦探们正在使用他们自己训练有素的眼睛，沿着基于人工智能（AI）的商业软件，来发现图像重复和其他可能暗示记录保存草率或更糟的问题。他们在PubPeer这样的在线论坛上揭露了这些担忧，PubPeer每天都有许多新的帖子标记形象问题。
Some of these efforts have led to action. Last month, for example, the Dana-Farber Cancer Institute (DFCI) in Boston, Massachusetts, said that it would ask journals to retract or correct a slew of papers authored by its staff members. The disclosure came after an observer raised concerns about images in the papers. The institute says it is continuing to investigate the concerns.
其中一些努力已导致采取行动。例如，上个月，位于马萨诸塞州波士顿的丹娜-法伯癌症研究所（DFCI）表示，它将要求期刊撤回或更正其工作人员撰写的大量论文。在一名观察员对报纸上的图像表示担忧之后，这一消息被披露。该研究所说，它正在继续调查这些问题。
That incident was just one of many. In the face of public scrutiny, academic journals are increasingly adopting tricks and tools, including commercial AI-based systems, to spot problematic imagery before, rather than after, publication. Here, Nature reviews the problem and how publishers are attempting to tackle it.
这一事件只是众多事件之一。面对公众的监督，学术期刊越来越多地采用技巧和工具，包括基于人工智能的商业系统，在出版之前而不是之后发现有问题的图像。在这里，《自然》杂志回顾了这个问题以及出版商如何试图解决这个问题。
What sorts of imagery problem are being spotted?
发现了什么样的图像问题？
Questionable image practices include the use of the same data across several graphs, the replication of photos or portions of photos, and the deletion or splicing of images. Such issues can indicate an intent to mislead, but can also result from an innocent attempt to improve a figure’s aesthetics, for example. Nonetheless, even innocent mistakes can be damaging to the integrity of science, experts say.
可疑的图像实践包括在多个图表中使用相同的数据，复制照片或照片的一部分，以及删除或拼接图像。这样的问题可能表明有意误导，但也可能是由于无辜的尝试，以改善一个数字的美学，例如。尽管如此，专家们说，即使是无辜的错误也会损害科学的完整性。
How prevalent are these issues, and are they on the rise?
这些问题有多普遍，它们是否在上升？
The precise number of such incidents is unknown. A database maintained by the website Retraction Watch lists more than 51,000 documented retractions, corrections or expressions of concern. Of those, about 4% flag a concern about images.
这类事件的确切数目不详。撤回观察网站维护的一个数据库列出了51 000多份记录在案的撤回、更正或关切表示。其中，约4%的人表示对图像的担忧。
One of the largest efforts to quantify the problem was carried out by Elisabeth Bik, a scientific image sleuth and consultant in San Francisco, California, and her colleagues1. They examined images in more than 20,000 papers that were published between 1995 and 2014. Overall, they found that nearly 4% of the papers contained problematic figures. The study also revealed an increase in inappropriate image duplications starting around 2003, probably because digital photography made it easier to alter photos, Bik says.
量化这一问题的最大努力之一是由加州旧金山弗朗西斯科的科学图像侦探和顾问伊丽莎白·比克和她的同事们进行的。他们研究了1995年至2014年间发表的2万多篇论文中的图像。总体而言，他们发现近4%的论文包含有问题的数据。Bik说，这项研究还显示，从2003年开始，不适当的图像复制有所增加，可能是因为数码摄影使修改照片变得更容易。
Modern papers also contain more images than do those from decades ago, notes Bik. “Combine all of this with many more papers being published per day compared to ten years ago, and the increased pressure put on scientists to publish, and there will just be many more problems that can be found.”
Bik指出，与几十年前相比，现代报纸包含的图像也更多。“与十年前相比，联合收割机将所有这些与每天发表的更多论文结合起来，以及科学家发表论文的压力增加，将会发现更多的问题。”
The high rate of reports of image issues might also be driven by “a rise in whistle-blowing because of the global community’s increased awareness of integrity issues”, says Renee Hoch, who works for the PLOS Publication Ethics team in San Francisco, California.
加州弗朗西斯科公共科学图书馆出版道德小组的Renee Hoch说，高比例的形象问题报告也可能是由于“全球社会对诚信问题的认识提高，举报增多”。
What happened at the Dana-Farber Cancer Institute?
丹娜-法伯癌症研究所发生了什么
In January, biologist and investigator Sholto David, based in Pontypridd, UK, blogged about possible image manipulation in more than 50 biology papers published by scientists at the DFCI, which is affiliated with Harvard University in Cambridge, Massachusetts. Among the authors were DFCI president Laurie Glimcher and her deputy, William Hahn; a DFCI spokesperson said they are not speaking to reporters. David’s blog highlighted what seemed to be duplications or other image anomalies in papers spanning almost 20 years. The post was first reported by The Harvard Crimson.
今年1月，英国庞蒂普里德的生物学家兼调查员肖尔托大卫在博客上发表了关于DFCI科学家发表的50多篇生物学论文中可能存在的图像操纵的文章。DFCI隶属于马萨诸塞州剑桥的哈佛大学。作者中有DFCI总裁劳里格利姆彻和她的副手威廉哈恩; DFCI发言人说，他们没有对记者说话。大卫的博客强调了近20年来论文中似乎存在的重复或其他图像异常。这篇文章最初是由《哈佛深红报》报道的。
The DFCI, which had already been investigating some of these issues, is seeking retractions for several papers and corrections for many others. Barrett Rollins, the DFCI’s research-integrity officer, says that “moving as quickly as possible to correct the scientific record is important and a common practice of institutions with strong research integrity”.
DFCI已经在调查其中的一些问题，正在寻求撤回几篇论文，并更正许多其他论文。DFCI的研究诚信官员巴雷特·罗林斯（Barrett Rollins）表示，“尽快采取行动纠正科学记录很重要，也是具有强大研究诚信的机构的常见做法”。
“It bears repeating that the presence of image duplications or discrepancies in a paper is not evidence of an author’s intent to deceive,” he adds.
他补充说：“值得重申的是，论文中存在图像重复或差异并不能证明作者意图欺骗。”
What are journals doing to improve image integrity?
期刊如何提高形象完整性？
In an effort to reduce publication of mishandled images, some journals, including the Journal of Cell Science, PLOS Biology and PLOS ONE, either require or ask that authors submit raw images in addition to the cropped or processed images in their figures.
为了减少错误处理图像的出版，一些期刊，包括《细胞科学杂志》、《PLOS生物学》和《PLOS ONE》，要求作者除了在他们的数字中提交裁剪或处理过的图像外，还提交原始图像。
Many publishers are also incorporating AI-based tools including ImageTwin, ImaCheck and Proofig into consistent or spot pre-publication checks. The Science family of journals announced in January it is now using Proofig to screen all its submissions. Holden Thorp, editor in chief of the Science family of journals, says Proofig has spotted things that led editors to decide against publishing papers. He says authors are usually grateful to have their errors identified.
许多出版商还将基于AI的工具，包括ImageTwin，ImaCheck和Proofig纳入一致或现场出版前检查。《科学》系列期刊今年1月宣布，它现在正在使用Proofig筛选所有提交的论文。《科学》系列期刊的主编霍尔顿索普说，Proofig发现了一些导致编辑们决定不发表论文的事情。他说，作者通常很感激他们的错误被发现。
What kinds of issues do these AI-based systems flag?
这些基于AI的系统会标记哪些问题？
All these systems can, for example, quickly detect duplicates of images in the same paper, even if those images have been rotated, stretched or cropped or had their colour altered.
例如，所有这些系统都可以快速检测同一张纸上的重复图像，即使这些图像已经旋转，拉伸或裁剪或颜色改变。
Different systems have different merits. Proofig, for example, can spot splices created by chopping out or stitching together portions of images. ImageTwin, says Bik, has the advantage of allowing users to cross-check an image against a large data set of other papers. Some publishers, including Springer Nature, are developing their own AI image-integrity software. (Nature’s news team is editorially independent of its publisher, Springer Nature.)
不同的制度有不同的优点。例如，Proofig可以发现通过切割或拼接图像部分而产生的拼接。Bik说，ImageTwin的优势在于允许用户将一张图片与其他论文的大量数据集进行交叉检查。包括Springer Nature在内的一些出版商正在开发自己的人工智能图像完整性软件。（《自然》的新闻团队在编辑上独立于出版商施普林格·自然。
Many of the errors flagged by AI tools seem to be innocent. In a study of more than 1,300 papers submitted to 9 American Association for Cancer Research journals in 2021 and early 2022, Proofig flagged 15% as having possible image duplications that required follow-up with authors. Author responses indicated that 28% of the 207 duplications were intentional — driven, for example, by authors using the same image to illustrate multiple points. Sixty-three per cent were unintentional mistakes.
人工智能工具标记的许多错误似乎是无辜的。在一项针对2021年和2022年初提交给美国癌症研究协会9种期刊的1，300多篇论文的研究中，Proofig将15%的论文标记为可能存在图像重复，需要与作者进行随访。作者的回应表明，207个重复中有28%是故意驱动的，例如，作者使用同一图像来说明多个点。63%是无意的错误。
How well do these AI systems work?
这些AI系统的工作效果如何？
Users report that AI-based systems definitely make it faster and easier to spot some kinds of image problems. The Journal of Clinical Investigation trialled Proofig from 2021 to 2022 and found that it tripled the proportion of manuscripts with potentially problematic images, from 1% to 3%2.
用户报告说，基于人工智能的系统确实可以更快、更容易地发现某些类型的图像问题。《临床研究杂志》从2021年到2022年试用了Proofig，发现它将具有潜在问题图像的手稿比例增加了两倍，从1%增加到3% 2 。
But they are less adept at spotting more complex manipulations, says Bik, or AI-generated fakery. The tools are “useful to detect mistakes and low-level integrity breaches, but that is but one small aspect of the bigger issue”, agrees Bernd Pulverer, chief editor of EMBO Reports. “The existing tools are at best showing the tip of an iceberg that may grow dramatically, and current approaches will soon be largely obsolete.”
但他们不太擅长发现更复杂的操纵，Bik说，或者人工智能生成的伪造。EMBO报告的主编Bernd Pulverer表示，这些工具“对于检测错误和低级别的完整性漏洞很有用，但这只是更大问题的一个小方面”。“现有的工具充其量只是冰山一角，可能会急剧增长，目前的方法很快就会过时。”
Are pre-publication checks stemming image issues?
出版前检查是否会导致图像问题？
A combination of expert teams, technology tools and increased vigilance seems to be working — for the time being. “We have applied systematic screening now for over a decade and for the first time see detection rates decline,” says Pulverer.
专家团队、技术工具和提高警惕的结合似乎正在发挥作用–就目前而言。“我们已经应用系统筛查十多年了，第一次看到检出率下降，”Pulverer说。
But as image manipulation gets more sophisticated, catching it will become ever harder, he says. “In a couple of years all of our current image-integrity screening will still be useful for filtering out mistakes, but certainly not for detecting fraud,” Pulverer says.
但他说，随着图像处理变得越来越复杂，捕捉它将变得越来越困难。“在几年内，我们目前所有的图像完整性筛选仍然可以用于过滤错误，但肯定不能用于检测欺诈，”Pulverer说。
How can image manipulation best be tackled in the long run?
从长远来看，如何才能最好地解决图像操纵问题？
Ultimately, stamping out image manipulation will involve complex changes to how science is done, says Bik, with more focus on rigour and reproducibility, and repercussions for bad behaviour. “There are too many stories of bullying and highly demanding PIs spending too little time in their labs, and that just creates a culture where cheating is ok,” she says. “This needs to change.”
Bik说，最终，消除图像操纵将涉及科学工作方式的复杂变化，更多地关注严谨性和可重复性，以及对不良行为的影响。她说：“有太多关于欺凌和高要求的PI在实验室里花的时间太少的故事，这只会创造一种作弊是可以的文化。”“这需要改变。”
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