时光飞逝,岁月如梭;蛇年渐去,马年将至.转瞬间,2025年已成尾声,2026新的一年正在向我们翩翩走来. 回顾2025年,我们坚守办刊宗旨,提升办刊能力.我们制定了《期刊质量与影响力建设提升方案》,剖析了影响因素,并明确了质量与影响力提升路径.同时,初步完成了"十五五"战略规划编制,其核心是研究和应用人工智能技术,全面审视和介入论文的评审、发布和评价过程.
[Purpose/Significance]Under the backdrop of the accelerated development of AI for Science(AI4S)and national strategies on"AI+Science and Technology",high-quality,computable corpus resources have become a critical factor for large-model pretraining and intelligent scientific discovery.As the social infrastructures,libraries are facing growing demands to transform toward the construction and provision of AI-oriented corpus resources and services.The article aims to clarify the annotation of the"AI corpus library"and to provide a reference framework for related theoretical research and practical implementation.[Method/Process]By employing conceptual and evo-lutionary analysis,the article clarifies the essential characteristics of the AI corpus library,interpreting it as a deep integration and functional reconstruction of"Database × Corpus × Digital Library".It analyzes functional require-ments from three dimensions:technological evolution,social application,and regulatory governance.Furthermore,by synthesizing the"text-as-data"model of HathiTrust and the"digital scholarship"practice of the British Library,the paper systematically summarizes the evolutionary logic of the transition from digital libraries to AI corpus li-braries.[Result/Conclusion]The study shows that the AI corpus library is a new type of knowledge infrastructure oriented toward"human-machine agent"entities,with multi-modal and computable corpora as its core organiza-tional objects.Its construction should follow an architectural system characterized by data-driven top-level logic,knowledge organization as the intermediate mechanism,and agent-based applications as the functional innovation.The corpusization of existing library collections,the establishment of"non-consumptive use"governance mecha-nisms,and the embedding of corpus services into digital scholarship workflows represent effective paths for librar-ies to achieve functional expansion and intelligent upgrading.
[Purpose/Significance]Major local science and technology projects generally reflect the will and strategic needs of the government,aiming to solve the"bottleneck"problems in key technical fields.These projects are characterized by their importance,scale,and specialization.Traditional methods of expert evaluation and statistical analysis can no longer meet the new requirements of the current artificial intelligence and big data.The comprehensive application of various evaluation methods,such as intelligence analysis and peer review,to conduct performance eval-uation can provide strong support for the planning management,and decision-making of local science and technology management departments.[Method/Process]This paper focuses on the major science and technology projects in Fu-jian Province to establish a performance evaluation index system based on six dimensions:project decision-making,implementation management,goal achievement,technical level,transformation effect,and sustainable impact.Next,it introduces a scientific and technological intelligence method to integrate intelligence analysis with scientific evalua-tions by supplementing the index system with technical intelligence-related indicators and adding intelligence analysis and evaluation to the evaluation process.Then,a comprehensive evaluation model based on the AHP and entropy weight cloud model is established.Finally,a case study of a specific project is used to verify the application value of the above method in the performance evaluation process of major local science and technology projects in Fujian Prov-ince.[Result/Conclusion]The research results demonstrate that the intelligence analysis and evaluation method re-duces the influence of expert subjectivity,making the evaluation results more accurate and objective.The AHP-entropy weigh-cloud model accounts for the fuzziness and uncertainty of the evaluation information,which helps to accurately evaluate the performance levels,quickly determine the key influencing factors,and further enhance the authenticity and effectiveness of evaluation results.So,the method proposed in this paper is applicable to the post-performance evaluation of major local science and technology projects.It can provide theoretical support and practical guidance for scientific and technological information agencies or other evaluation institutions.
[Purpose/Significance]Academic papers are the main form of disseminating and validating scientific knowledge.Integrating such knowledge into policymaking can improve the scientificity and rationality of documents.By evaluating the policy impact,it can effectively demonstrate how academic papers can be transformed into policy and explore a new perspective on the evaluation of academic paper impact.[Method/Process]This paper adopts text mining methods,such as Sentence-BERT,SBERTopic to construct an indicator system for evaluating policy impact of academic papers based on semantic association from three dimensions:mention-level,thematic potential,and sentence-level im-pact.An empirical analysis is conducted on academic papers and policy texts in artificial intelligence from 2010 to 2024.The entropy weight-TOPSIS method is applied to weight the indicators for a composite policy impact score.[Result/Conclusion]Only a few papers reveal high policy impact,with their topic distribution and content exhibiting a clear ten-dency.Under different evaluation criteria,there are significant differences in the influence of papers in the field of artificial intelligence.In the future,scholars and policymakers should collaborate to address the challenges in translating academic research into policy,establish and improve the platform of government think tanks,promote more and faster academic papers into the policy-making process,and explore a more comprehensive and effective evaluation system.
[Purpose/Significance]This study investigates the adaptability and evolutionary path of agent technologies in science and technology(S&T)intelligence work,aiming to meet the increasing demands for intel-ligent and collaborative systems.It introduces the concept of the Documentation and Information Service Agent(DIS Agent)and clarifies its theoretical foundation and system mechanisms,providing methodological support for advancing S&T intelligence systems toward higher-level cognitive capabilities.[Method/Process]Drawing on the stratification of agent capabilities and multi-agent collaboration models,the study examines their development in scientific and intelligence contexts.It proposes a three-stage system evolution path-from Management Infor-mation Systems(MIS),through AI Agent systems,to the Agentic AI paradigm-within the three major domains of information management,intelligence analysis,and scholarly communication.A task-closed-loop architecture is proposed to support the emergence of human-multi-agent collaboration mechanisms.[Result/Conclusion]DIS Agents are task-oriented systems that integrate multiple types of agents with large language models as cognitive cores,characterized by modular design and collaborative evolution capabilities.Under this architecture,the three core domains of intelligence work undergo a shift from rule-based configuration to semantic-driven systems,en-abling task-oriented knowledge organization,autonomous strategy generation,and optimized communication loops.The role of human experts evolves from operators to"intent architect for DIS task framework"and"process quality supervisors,"marking the formation of a new paradigm of human-multi-agent collaboration.Future work will focus on the development and practical deployment of DIS Agent systems.
[Purpose/Significance]With the rapid development of artificial intelligence(AI)technology,the penetration rate of AI assistants continues to increase in industries such as retail,finance,and healthcare.The influ-ence mechanism of users on their usage intention has also attracted extensive attention from scholars.User trust is an important driving factor for the product adoption,but the existing research has not yet reached a consensus on the key influencing factors of trust and their effects.So,a systematic review and evaluation of these factors is urgently needed.[Method/Process]The study took 65 empirical research papers published at home and abroad as samples.It quantitatively analyzed the factors influencing user trust in AI assistants and its relationship between trust and use intention using meta-analysis.Then,it tested the moderating effect of user cultural background and product usage scenarios on this relationship.[Result/Conclusion]The results show that product anthropomorphic traits,perceived usefulness,perceived ease of use,social presence,social influence,product performance and perceived risk are sev-en important factors influencing user trust.Perceived risk has a significantly negative impact on user trust,the other factors have a significantly positive impact on user trust.In addition,user trust has a significantly positive impact on usage intention,but there is some heterogeneity among different studies.Through moderating effect analysis,it finds that user cultural background and AI assistant product use scenarios are the main reasons for heterogeneity.The research provides a theoretical basis for future in-depth studies and offer guiding suggestions for the interactive design and promotion of AI assistant products.
[Purpose/Significance]This paper analyzes the experience of building public trust in the open utilization of health data in the UK,aiming to provide insights and references for global health data governance.[Method/Process]By employing online research and case study methods,and based on the hierarchy model of public trust,this study deconstructed the UK's practice of building public trust in the open utilization of health data.It summarized the effectiveness and challenges of the UK's approach and offered forward-looking suggestions in light of the current state of health data open utilization in China.[Result/Conclusion]The UK's approach deeply highlights the necessity,hierarchy,and long-term nature of building public trust.The hierarchy model of public trust provides a theoretical guide and an implementation roadmap for the public trust.At present,China should focus on authorized operation of public data to promote the compliant and lawful utilization of health data.It should actively advance the construction of trusted health data spaces to address issues related to data security and privacy protec-tion.Moreover,China should explore the implementation of Date Use Register systems and standards to enhance the transparency of health data utilization.At the same time,drawing on the hierarchy model of public trust and considering China's national conditions,forward-looking research and design should be carried out in three areas:public benefit,opt-out choices,and public involvement.
[Purpose/Significance]A moderate allocation method can help university libraries distribute print book purchases more reasonably among various disciplines.[Method/Process]Due to the allocation dilemma of print book purchases in various disciplines in libraries,this study combined circulation rate,funding guarantee rate,and the ratio of professional books to non-professional books to establish a moderate allocation model between the purchases volume for professional discipline books and the books needed to meet reader demand.Furthermore,based on the discipline-specific factors,it established a model for distributing discipline-specific books among different disciplines.Finally,based on the books borrowing situation,it established a moderate allocation for the purchase of books needed to meet readers' needs in various disciplines.[Result/Conclusion]Through the practice of print book purchase decision-making at Hunan University of Science and Technology Library,this study proves that the moder-ate allocation model is a complete and reasonable allocation framework,achieving the basic guarantee of profession-al discipline books,a relative balance in meeting reader borrowing need,and an improved circulation rate for print books.
[Purpose/Significance]The Altmetrics data generation process is explained from the perspective of information behavior.Based on this,discovering,identifying and digging out the main dilemmas in the devel-opment of Chinese Altmetrics can provide important references and practical guidance for fostering the application scenarios of Altmetrics in Chinese academic ecology.[Method/Process]Taking the process of Altmetrics proposal and connotation transmutation as the logical starting point of the research,this paper analyzed the generation pro-cess of Altmetrics data from the perspective of user information behavior,and combined the special characteristics of Chinese online social platform environment.It summarized the development dilemmas of Chinese Altmetrics and put forward corresponding countermeasure suggestions.[Result/Conclusion]Altmetrics data is the result of the information behavior of various stakeholders relying on network platforms.On the one hand,it reflects the accumu-lation of data in each stage of the life cycle of a single user's information behavior,and on the other hand,it reflects the synergistic and overlapping emergence process of the information behavior of a large number of stakeholders centered on the network platform.The alienation of scientific communication function is the main reason for the predicament of Chinese Altmetrics development,which is centrally manifested in:the lack of endogenous motiva-tion for Altmetrics development,the lack of consensus among the relevant stakeholders for Altmetrics development,and the lack of data aggregation tools for Altmetrics development.Countermeasures can be taken to break through the Altmetrics development dilemma by building multiple incentives and synergistic mechanisms,strengthening consensus and collaboration,and building an intelligent data integration and analysis platform.
[Purpose/Significance]The high-quality transformation and development of libraries urgently re-quire the support of cutting-edge technologies and the implementation of new development concepts.Taking data as the key production factor,new quality productive forces is led by technological innovation,takes and supported by new technologies such as digitalization,networking,and intelligence.It provides a powerful impetus and essential support for the construction of metaverse libraries.It is of profound strategic significance and practical value to ac-tively build metaverse libraries and cultivate and develop new quality productive forces.[Method/Process]Using logical and content analysis methods,and starting from the framework of productivity composition in Marx's classi-cal theory,this study elaborated on the internal logic,practical dilemmas,and development paths of the bidirection-al empowerment between new quality productive forces and metaverse libraries.[Result/Conclusion]It suggests that measures be taken to achieve bidirectional empowerment between the new quality productivity and metaverse libraries,including comprehensively deepening reforms,improving institutional mechanisms and systems;priori-tizing education,accelerating the cultivation of new talents;adhering to innovation-driven development,promoting the application of emerging technologies;and exploring the value of data to unleash the potential of data elements.
[Purpose/Significance]From the dual perspectives of preprint platforms and librarians,this paper aims to elucidate the current situation,impact,and library strategies for preprint review and refereed preprints,providing references for Chinese preprint platforms to conduct preprint review.[Method/Process]Using online research methods,this paper analyzed the concepts,emerging characteristics,and impacts of preprint review and refereed preprints on traditional scholarly communication systems.It then examined the implications for libraries and corresponding strategies from a library perspective.[Result/Conclusion]Preprint review and refereed preprints have influenced the resource construction and preservation of libraries,changing users'research information needs,and affecting the direction of libraries'and librarians'endeavors in open access.Libraries,which are not only the promoters,builders and operators of preprints and preprint platforms,but also the funders and technical supporters of preprint review services,should actively engage in metadata development,indexing tool creation,coordinating in preprint review,and conducting relevant trainings to support its healthy development and promote a virtuous cycle in the scholarly communication ecosystem.
[Purpose/Significance]In order to comply with the trend of high-quality management of agricultural scientific data,and to ensure the transparency and trustworthiness of agricultural scientific data traceability,a concep-tual framework of blockchain-based trusted traceability of agricultural scientific data is constructed.[Method/Process]A four-layer framework of trusted traceability for agricultural science data,FRTASD,was constructed based on the current requirements of trusted traceability and related theories.[Result/Conclusion]This framework logically pro-vides a new idea for the reliable traceability of agricultural scientific data.At the same time,an attempt is made for the reliable traceability of rice scientific data through the investigation of agricultural scientific research websites.
[目的 /意义]基于学者知识结构蕴含的创新特征，设计学者早期知识结构新颖性的测度指标，以此预测学者未来的影响力，为学术人才的早期识别提供新的指标借鉴。[方法 /过程]首先，通过Pub Med Knowledge Graph数据库获取57 927位生物医学领域学者数据，利用受控主题词共现关系构建学者的知识结构；其次，从知识主题与结构位置两个层面出发设计6项指标测度学者早期知识结构新颖性；之后，根据学者后期的影响力对学者进行分类标注，训练机器学习模型；最后，实验评估不同组合变量模型下的分类效果，分析基于知识结构新颖性指标的预测性能。[结果 /结论 ]新颖性指标能有效预测影响力；单指标预测中，主题新颖性（TN）效果最好，结构层面的4个指标效果均超过主题组合新颖性（TCN）；综合指标的预测F1值平均提高2.7%。从内容特征角度出发，为预测与理解学者学术影响力提供新视角，所设计的新指标具有实用价值，能帮助弥补现有预测指标的不足。
[Purpose/Significance]By developing a user experience scale for mobile short video APP,this paper provides reliable suggestions for the sustainable development of mobile short video APP.[Method/Process]Based on the theory of perceived affordance,a qualitative scale was constructed based on literature research and group discussion.The scale was quantitatively optimized through pre-investigation,and data were obtained through formal investigation.Exploratory factor analysis and confirmatory factor analysis were carried out on the effec-tive data,and the formal scale was revised and formed.[Result/Conclusion]The formal scale includes five main dimensions,10 sub-dimensions and 30 items,including perceived physical affordance,perceived cognitive affor-dance,perceived emotional affordance,perceived control affordance and perceived interaction affordance.It is used to measure the user experience level of mobile short video APP.
[Purpose/Significance]This study investigates documentation requirements in cultural heri-tage policies to understand their overall status,main content,and future development trends.[Method/Pro-cess]The study adopted network literature survey and policy content analysis to code and analyze 148 policy documentation requirements related to cultural heritage documentation in China.[Result/Conclusion]It finds that,with the development of these policies in China,the framework of policies has been formed,including the strong demand of documentation,the synergistic participation of multiple stakeholders,expanding and de-tailed documentation objects,access-oriented cultural heritage archiving activities,and sustained and complete safeguard measures.Overall,documentation is becoming an indispensable and fundamental part of cultural heritage protection.In the future,it is necessary to further strengthen the systematization and relevance,the professionalism and digital transformation-oriented design of policies.
[Purpose/Significance]This paper probes into the factors influencing open science policy formula-tion in research institutions,points out the key issues,and offers recommendations for Chinese research institutions.[Method/Process]Firstly,the qualitative research method is adopted to construct the theoretical model of the fac-tors influencing open science policy formulation in research institutions.Then a questionnaire survey is carried out based on the model,and the key issues of policy formulation are pointed out,and specific suggestions are provided for policy formulation.[Result/Conclusion]The formulation of open science policy in research institutions needs to conform to the national policy orientation,clarify the guiding principles of the policy,improve the decision-mak-ing and judgment ability,balance and coordinate the interests of multiple stakeholders,and guarantee the input of material resources,so as to give full play to the main role of research institutions in the process of open science.
[Purpose/Significance]The term"Tu Shu Guan"in Chinese is the most fundamental and pivotal term in library science in China.Its etymological attributes represent one of the significant issues that cannot be ig-nored in the study of Chinese library history.The objective of this paper is to elucidate the etymology of the term"Tu Shu Guan"to delineate its dissemination in China and Japan,and to ascertain its linguistic attributes,which will facilitate a more profound understanding of Chinese library history.[Method/Process]This paper used methods of textology,bibliography,and etymology to review the academic history and examine its initial documentary evi-dence for the term,and examples of its use during the Ming and Qing dynasties.As books were the most important carrier for the dissemination of the term,a systematic analysis of Huang Tingjian's poems in Japan was conducted to investigate the annotation and publication activities of the poems and to analyze the stereotypes and popularity of the term"Tu Shu Guan"in China and Japan in the modern era.The etymological attributes of the term were then argued from an etymological point of view using the etymological research method.[Result/Conclusion]From an etymological perspective,it can be argued that a term is a"returned word"(Sino-Japanese interactive word),as long as a term originally appeared in Chinese literature,was later introduced to Japan,and was adopted by the Japanese during the Meiji period as a translation of a Western term.Thus,the term"Tu Shu Guan"is not a"Japanese word"but a"returned word,"or"Sino-Japanese interactive word".
[Purpose/Significance]Trust among relevant stakeholders has become a key factor in determin-ing the successful open utilization of healthcare big data.This study investigates the impact mechanism of trust on the stakeholder behavior,considering the factors of trust gains and losses,providing forward-looking references for improving the effectiveness of healthcare big data open use in China.[Method/Process]Focusing on the deci-sion-making behavior of the data platform,users,and patients,and considering factors of trust gains and losses,this study established a tripartite evolutionary game model based on the analysis of the open utilization process.Simu-lation analysis was conducted using MATLAB,and countermeasure suggestions were proposed based on the equi-librium point analysis and simulation results.[Result/Conclusion]Gaining the trust of patients is fundamental for users to transparently use data.Enhancing the security of the research environment can fundamentally solve trust issues.Strengthening regulation and increasing the trust gains and losses for users contribute to a positive state of open utilization.While raising the trust level of patients in data platforms,it is more crucial to intensify constraints on user behavior.China may consider building a nationally-led platform for the open utilization of healthcare big data,strengthening the construction of a trusted research environment and actively promoting its application,im-plementing a data use registration system,and establishing a standard system,for effectively guiding the public to participate the collaborative governance of healthcare big data.
[Purpose/Significance]The data-driven era faces many challenges such as difficulties in data cognition,obscure interpretation results,and insufficient credibility of model decision-making.The data sto-rytelling method that integrates interpretable results provides theoretical support and solutions to address the challenges and enhance the value of data utilization.[Method/Process]This paper summarizes the interpre-tation form of model-agnostic local interpretability technology,the narrative structure of data stories and the methods used in the current research on data storytelling.Based on the interpretability theory and the realiza-tion mode of data storytelling,a data storytelling model of"extraction-reorganization-narrative"is construct-ed,and the data story mapping process is given by using the defined element tuple.The key techniques of story model design are introduced briefly.[Result/Conclusion]Based on the theory of data storytelling model design,this paper proposes a"fan-shaped"storytelling implementation path for interpretation results and an interactive framework that integrates the elements of interpretation results and storytelling model,and reflects the practical value of data storytelling method in result interpretation through case studies.A framework of data storytelling methods based on interpretable results is constructed,which provides new ideas for expand-ing storytelling paths with data perception and cognition and assisting intelligent decision-making.
[Purpose/Significance]This study aims to extract structured item information from free-text clin-ical scales using ChatGPT without annotations,which efficiently advances the structuring and intellectualization of medical scale resources.[Method/Process]A framework for item information extraction was defined,including eight attribute types and considering the structural differences in clinical scale measurement concepts.A dataset was constructed by collecting 59 commonly used clinical psychometric assessment scale documents.Zero-shot prompt templates were designed based on measurement concept levels,and experiments were conducted using the official ChatGPT-3.5 and ChatGPT-4 interfaces.The extraction performance and possible influencing factors of different ChatGPT versions in processing different clinical scale texts were analyzed from multiple perspectives.[Result/Conclusion]The extraction performance for scale item sources is the best,with Micro-F1 and Macro-F1 scores of at least 98.90％and 97.83％,respectively.This is followed by response options,instructional guidance,and scoring rules,with item numbers and instructions showing moderate performance.Clinical explanations have the lowest performance,with Micro-F,and Macro-F,scores of 47.73％and 45.51％,respectively.ChatGPT-4 performs better overall,but the recall rate of some attributes is weaker than that of ChatGPT-3.5.The increase in measurement con-cept levels,dimensionality,number of items,and text length are found to reduce model performance.In summary,ChatGPT can efficiently assist in the structuring of medical scale resources,especially when dealing with simple scales.
