摘要：
【目的】调查机器翻译在医学论文摘要翻译中的应用现状，识别关键问题，并探索有效的机器翻译协同路径。【方法】采用问卷调查法，面向医学期刊编辑和作者收集关于机器翻译的认知、使用行为和质量评价的数据。【结果】共收集193名编辑和489名作者的数据。93.66%的作者和87.57%的编辑会在学术翻译中使用在线机器翻译，并有系统偏好。90.68%的编辑接受机器翻译作为辅助工具，75.65%认为其在一定程度上可减轻工作量。61.14%的编辑、44.58%的作者会在机器翻译前积极优化原文；58.69%的作者表示有译后编辑，但只有29.02%的编辑认可作者于投稿前进行译后编辑。51.12%的作者和29.02%的编辑对机器翻译加作者修改的摘要质量表示满意；编辑审校后的摘要质量得到70.46%的编辑和42.74%的作者的较高评价。【结论】机器翻译在医学论文摘要翻译中被广泛采用，但存在使用习惯和质量评价差异。建议建立从作者到编辑的协同路径，培养机器翻译有效使用能力，以促进机器翻译与医学科技期刊出版的深度融合，提高翻译质量和效率。
关键词:
医学科技期刊,
机器翻译,
英文摘要,
人工智能
Abstract:
［Purposes］ This study aims to investigate the current application status of machine translation (MT) in the translation of medical paper abstracts, identify key issues, and explore effective collaborative pathways for MT. ［Methods］ We conducted a questionnaire survey to collect data from medical journal editors and authors regarding their awareness, usage behavior, and quality evaluation of MT. ［Findings］ Data are collected from 193 editors and 489 authors in this survey. Totally 93.66% of authors and 87.57% of editors use online MT for academic translation and have system preferences. 90.68% of editors accept MT as an auxiliary tool, and 75.65% consider that it has reduced their workload to a certain degree. 61.14% of editors and 44.58% of authors actively optimize the original text before using MT. 58.69% of authors state that they conduct post-editing, but only 29.02% of editors recognize that authors have done post-editing before submission. 51.12% of authors and 29.02% of editors are satisfied with the quality of abstracts after MT and author modifications. The quality of abstracts after editorial review is highly rated by 70.46% of editors and 42.74% of authors. ［Conclusions］ MT is widely adopted in the translation of medical paper abstracts, but differences exist in usage habits and quality evaluations. It is recommended to establish a collaborative pathway from authors to editors, cultivate the ability to use MT effectively, and promote the in-depth integration of MT into the publication of medical scientific journals, so as to improve translation quality and efficiency.
Key words:
Medical scientific journal,
Machine translation,
English abstract,
Artificial intelligence
夏玲, 向晓莉, 李宜蔓, 吴虹丽, 李宜博, 刘爽. 机器翻译医学论文摘要的现状分析及作者与编辑协同路径研究[J]. 中国科技期刊研究, 2024, 35(12): 1757-1766.
XIA Ling, XIANG Xiaoli, LI Yiman, WU Hongli, LI Yibo, LIU Shuang. Current application status of machine translation in medical paper abstracts and collaborative pathway between authors and editors[J]. Chinese Journal of Scientific and Technical Periodicals, 2024, 35(12): 1757-1766.