Medical Writing and Research Methodology for the Orthopaedic Surgeon

This unique guide is designed to facilitate the complex task of getting a paper published in an orthopaedics journal. The editors have enlisted expert orthopaedic surgeons from prestigious academic institutions, who share essential advice on how to set up and write on your research. The book addresses fraud issues, the correct use of English and editing, how to develop a sound research methodology, and editors’ and reviewers’ expectations, along with the main reasons for rejection. The future of the Impact Factor, altmetrics and Open Access journals are also discussed, and will be of special interest to young faculty who are starting their research career. The chapters are structured in a reproducible and easy-to-follow format. In addition, the editors offer tips and tricks for non-native speakers writing in English. As such, the book provides an accessible and comprehensive resource for all those seeking guidance on how to publish their research work in the field of orthopaedics. Plagiarism Is A Problem With Far-reaching Consequences For The Sciences. However, Even Today’s Best Software-based Systems Can Only Reliably Identify Copy&paste Plagiarism. Disguised Plagiarism Forms, Including Paraphrased Text, Cross-language Plagiarism, As Well As Structural And Idea Plagiarism Often Remain Undetected. This Weakness Of Current Systems Results In A Large Percentage Of Scientific Plagiarism Going Undetected. Bela Gipp Provides An Overview Of The State-of-the Art In Plagiarism Detection And An Analysis Of Why These Approaches Fail To Detect Disguised Plagiarism Forms. The Author Proposes Citation-based Plagiarism Detection To Address This Shortcoming. Unlike Character-based Approaches, This Approach Does Not Rely On Text Comparisons Alone, But Analyzes Citation Patterns Within Documents To Form A Language-independent Semantic Fingerprint For Similarity Assessment. The Practicability Of Citation-based Plagiarism Detection Was Proven By Its Capability To Identify So-far Non-machine Detectable Plagiarism In Scientific Publications. Contents Current State Of Plagiarism Detection Approaches And Systems Citation-based Plagiarism Detection target Groups Readers Interested In The Problem Of Plagiarism In The Sciences Faculty And Students From All Disciplines, But Especially Computer Science The Author Bela Gipp Is A Postdoctoral Researcher At The University Of California, Berkeley. By Bela Gipp. Plagiarism is a problem with far-reaching consequences for the sciences. However, even today's best software-based systems can only reliably identify copy & paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plagiarism often remain undetected. This weakness of current systems results in a large percentage of scientific plagiarism going undetected. Bela Gipp provides an overview of the state-of-the art in plagiarism detection and an analysis of why these approaches fail to detect disguised plagiarism forms. The author proposes Citation-based Plagiarism Detection to address this shortcoming. Unlike character-based approaches, this approach does not rely on text comparisons alone, but analyzes citation patterns within documents to form a language-independent "semantic fingerprint" for similarity assessment. The practicability of Citation-based Plagiarism Detection was proven by its capability to identify so-far non-machine detectable plagiarism in scientific publications. Contents Current state of plagiarism detection approaches and systems Citation-based Plagiarism Detection Target Groups Readers interested in the problem of plagiarism in the sciences Faculty and students from all disciplines, but especially computer science The Author Bela Gipp is a postdoctoral researcher at the University of California, Berkeley