Beyond authorship: Analyzing contributions in PLOS ONE and the challenges of appropriate attribution

Purpose:This study aims to evaluate the accuracy of authorship attributions in scientific publications,focusing on the fairness and precision of individual contributions within academic works.Design/methodology/approach:The study analyzes 81,823 publications from the journal PLOS ONE,covering the period from January 2018 to June 2023.It examines the authorship attributions within these publications to try and determine the prevalence of inappropriate authorship.It also investigates the demographic and professional profiles of affected authors,exploring trends and potential factors contributing to inaccuracies in authorship.Findings:Surprisingly,9.14%of articles feature at least one author with inappropriate authorship,affecting over 14,000 individuals(2.56%of the sample).Inappropriate authorship is more concentrated in Asia,Africa,and specific European countries like Italy.Established researchers with significant publication records and those affiliated with companies or nonprofits show higher instances of potential monetary authorship.Research limitations:Our findings are based on contributions as declared by the authors,which implies a degree of trust in their transparency.However,this reliance on self-reporting may introduce biases or inaccuracies into the dataset.Further research could employ additional verification methods to enhance the reliability of the findings.Practical implications:These findings have significant implications for journal publishers,Beyond authorship:Analyzing contributions in PLOS ONE and Maddi,A.,&the challenges of appropriate attribution highlighting the necessity for robust control mechanisms to ensure the integrity of authorship attributions.Moreover,researchers must exercise discernment in determining when to acknowledge a contributor and when to include them in the author list.Addressing these issues is crucial for maintaining the credibility and fairness of academic publications.Originality/value:This study contributes to an understanding of critical issues within academic authorship,shedding light on the prevalence and impact of inappropriate authorship attributions.By calling for a nuanced approach to ensure accurate credit is given where it is due,the study underscores the importance of upholding ethical standards in scholarly publishing.

Guide for Authors

Introduction Types ofpaper Contributions falling into the following categories will be considered for publication:Reviews,Technical papers,Theoretical papers,and Editorial.Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

Information for Authors

Chinese Phaysics Letters(CPL)is a peer-reviewed,inter-national and multidisciplinary journal sponsored by the Chi-nese Phaysical Society(CPS)and Institute of Physics,CAS,and hosted online by IOP Publishing Ltd.Launched in 1984 asthe flagship journal of CPS,CPL has become one of the mostprestigious periodicals published in China,and been among thegood choices for worldwide physicists to disseminate their mostimportant breakthroughs.

Information for Authors

Chinese Physics Letters(CPL)is a peer-reviewed,international and multidisciplinary journal sponsored by the Chinese Physical Society(CPS)and Institute of Physics,CAS,and hosted online by IOP Publishing Ltd.Launched in 1984 as the flagship journal of CPS,CPL has become one of the most prestigious periodicals published in China.

Information for Authors

General Journal of Beijing Institute of Technology(JBIT)is a periodical publication on science and technology published by Beijing Institute of Technology under the sponsorship of the Ministry of Industry and Information Technology of the People's Republic of China.JBIT was inaugurated in 1992.

Information for Authors

General Journal of Bejing Institute of Technology(JBIT)is a periodical publication on science andtechnology published by Beijing Institute of Technology under the sponsorship of the Ministry ofIndustry and Information Technology of the People's Republic of China.JBIT was inaugurated in 1992.

Information for Authors

General Journal of Bejing Institute of Technology(JBIT)is a periodical publication on science andtechnology published by Beijing Institute of Technology under the sponsorship of the Ministry ofIndustry and Information Technology of the People's Republic of China.JBIT was inaugurated in 1992.

Instructions for Authors

The Chinese Journal of Multiple Organ Diseases in the Elderly(Zhonghua Laonian Duoqiguan Jibing Zazhi)(ISSN 1671-5403)is launched in 2002 and published monthly by Chinese PLA General Hospital in Beijing,China.

High-speed Railway Guide for Authors

Types of paper Contributions falling into the following categories will be considered for publication:Original research papers,reviews,etc.Please ensure that you select the appropriate article type from the list of options when making your submission.Authors contributing to special issues should ensure that they select the special issue article type from this list.

A Novel Method for Resolving and Completing Authors' Country Affiliation Data in Bibliographic Records

Purpose: Our work seeks to overcome data quality issues related to incomplete author affiliation data in bibliographic records in order to support accurate and reliable measurement of international research collaboration(IRC).Design/methodology/approch: We propose, implement, and evaluate a method that leverages the Web-based knowledge graph Wikidata to resolve publication affiliation data to particular countries. The method is tested with general and domain-specific data sets.Findings: Our evaluation covers the magnitude of improvement, accuracy, and consistency. Results suggest the method is beneficial, reliable, and consistent, and thus a viable and improved approach to measuring IRC.Research limitations: Though our evaluation suggests the method works with both general and domain-specific bibliographic data sets, it may perform differently with data sets not tested here. Further limitations stem from the use of the R programming language and R libraries for country identification as well as imbalanced data coverage and quality in Wikidata that may also change over time.Practical implications: The new method helps to increase the accuracy in IRC studies and provides a basis for further development into a general tool that enriches bibliographic data using the Wikidata knowledge graph.Originality: This is the first attempt to enrich bibliographic data using a peer-produced, Webbased knowledge graph like Wikidata.

Information for Authors

General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.Cover Letters The journal requires a cover letter be included in submissions.A cover letter should explain why this topic is important,why these results are significant and what the novelty of this work is.

Information for Authors

General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.Cover Letters The journal requires a cover letter be included in submissions.A cover letter should explain why this topic is important,why these results are significant and what the novelty of this work is.

Information for Authors

General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.Cover Letters The journal requires a cover letter be included in submissions.A cover letter should explain why this topic is important,why these results are significant and what the novelty of this work is.

Information for Authors

General Rules Journal of Polyphenols publishes research articles,reviews and short communications in English,on the fields of the science and technology of plant polyphenols.

A novel method for clustering cellular data to improve classification

Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.

A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly increased.However,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient encryption.This paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative data.Each bundle includes updated information,allowing only the updated portions to be reencrypted when changes occur.The encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates occur.The proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext data.By utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those sections.This approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data environments.To validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size varied.Results show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size increases.Additionally,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

Impact of ocean data assimilation on the seasonal forecast of the 2014/15 marine heatwave in the Northeast Pacific Ocean

A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.

Synthetic data as an investigative tool in hypertension and renal diseases research

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

Peculiarities of gender disambiguation and ordering of non-English authors’names for Economic papers beyond core databases

Purpose:To supplement the quantitative portrait of Ukrainian Economics discipline with the results of gender and author ordering analysis at the level of individual authors,special methods of working with bibliographic data with a predominant share of non-English authors are used.The properties of gender mixing,the likelihood of male and female authors occupying the first position in the authorship list,as well as the arrangements of names are studied.Design/methodology/approach:A data set containing bibliographic records related to Ukrainian journal publications in the field of Economics is constructed using Crossref metadata.Partial semi-automatic disambiguation of authors’names is performed.First names,along with gender-specific ethnic surnames,are used for gender disambiguation required for further comparative gender analysis.Random reshuffling of data is used to determine the impact of gender correlations.To assess the level of alphabetization for our data set,both Latin and Cyrillic versions of names are taken into account.Findings:The lack of well-structured metadata and the poor use of digital identifiers lead to numerous problems with automatization of bibliographic data pre-processing,especially in the case of publications by non-Western authors.The described stages for working with such specific data help to work at the level of authors and analyse,in particular,gender issues.Despite the larger number of female authors,gender equality is more likely to be reported at the individual level for the discipline of Ukrainian Economics.The tendencies towards collaborative or solo-publications and gender mixing patterns are found to be dependent on the journal:the differences for publications indexed in Scopus and/or Web of Science databases are found.It has also been found that Ukrainian Economics research is characterized by rather a non-alphabetical order of authors.Research limitations:Only partial authors’name disambiguation is performed in a semi-automatic way.Gender labels can be derived only for authors declared by full First names or gender-specific Last names.Practical implications:The typical features of Ukrainian Economic discipline can be used to perform a comparison with other countries and disciplines,to develop an informed-based assessment procedure at the national level.The proposed way of processing publication data can be borrowed to enrich metadata about other research disciplines,especially for non-English speaking countries.Originality/value:To our knowledge,this is the first large-scale quantitative study of Ukrainian Economic discipline.The results obtained are valuable not only at the national level,but also contribute to general knowledge about Economic research,gender issues,and authors’names ordering.An example of the use of Crossref data is provided,while this data source is still less used due to a number of drawbacks.Here,for the first time,attention is drawn to the explicit use of the features of the Slavic authors’names.

基于人工智能的小说自编辑平台--Authors A.I.个案研究

人工智能在自然语言理解和生成上不断取得突破,在出版领域的应用也随之逐渐深入。基于这些人工智能技术的Authors A.I.能够自动阅读和评价小说作品,甚至提出改进意见,因此实际上可视为作者的自编辑平台,或者出版企业的编辑辅助平台。本文介绍其从一本书到一家公司的创立过程,以及支撑该平台运行的自然语言和技术原理;阐述了其所提供的AI分析报告,特别是叙事原型和情节转折、叙事节拍和叙事进程、主要人物性格和主题分析以及情绪色轮等要素的可视化分析;最后指出人工智能的发展为出版业提供了很好的机遇,基于AI,出版价值链有望在各方面得到改进。