In this study, we systematically elucidate the background and functionality of the Scilit database and evaluate the feasibility and advantages of the comprehensive impact metrics I3 and I3/N, introduced within the Scilit framework. Using a matched dataset of 17,816 journals, we conduct a comparative analysis of Scilit I3/N, Journal Impact Factor, and CiteScore for 2023 and 2024, covering descriptive statistics and distributional characteristics from both disciplinary and publisher perspectives. The comparison reveals that the Scilit I3 and I3/N framework significantly outperforms traditional mean-based metrics in terms of coverage, methodological robustness, and disciplinary fairness. It provides a more accurate, diagnosable, and responsible solution for interdisciplinary journal impact assessment. Our research serves as a "getting started guide" for Scilit, offering scholars, librarians, and academic publishers in the fields of bibliometrics or scientometrics a valuable perspective for exploring I3 and I3/N within an inclusive database. This enables a more accurate and comprehensive understanding of disciplinary development and scientific progress. We advocate for piloting and validating this method in broader evaluation contexts to foster a more precise and diverse representation of scientific progress.

翻译：本研究系统阐述了Scilit数据库的背景与功能，评估了在Scilit框架下引入的综合影响力指标I3及I3/N的可行性与优势。通过17,816种期刊的匹配数据集，我们对2023年与2024年的Scilit I3/N、期刊影响因子及CiteScore进行了比较分析，涵盖描述性统计与分布特征，并从学科和出版商视角展开探讨。比较结果表明，Scilit I3及I3/N框架在覆盖范围、方法稳健性和学科公平性方面显著优于传统的基于均值的指标，为跨学科期刊影响力评估提供了更精确、可诊断且负责任的解决方案。本研究可作为Scilit的"入门指南"，为文献计量学或科学计量学领域的学者、图书馆员及学术出版商提供在包容性数据库中探索I3与I3/N的宝贵视角，从而更准确、全面地理解学科发展与科学进步。我们建议在更广泛的评估场景中试点并验证该方法，以促进对科学进展更精确和多元化的呈现。