Chế tạo các kết quả nghiên cứu có thể được ngăn chặn? Xem xét ngang hàng có thể được tăng cường với việc kiểm tra tự động? Những câu hỏi này trở nên quan trọng hơn với sự gia tăng trong trình tự động dữ liệu với cổng. Tính hữu ích tiềm năng của mô hình thích hợp để phát hiện ít nhất là một số hình thức hoặc "quản lý kết quả 'cố ý hoặc vô ý là kiểm tra ở đây. Định luật Benford là một mối quan hệ phân phối giả định về tần số của chữ. | Chapter 12 Fraud Can the fabrication of research results be prevented Can peer review be augmented with automated checking These questions become more important with the increase in automated submission of data to portals. The potential usefulness of niche modeling to detecting at least some forms of either intentional or unintentional result management is examined here. Benford s Law is a postulated distributional relationship on the frequency of digits Ben38 . It states that the distribution of the combination of digits in a set of random data drawn from a set of random distributions follows the log relationship for each of the digits as shown in the Figure . Benford s Law actually more of a conjecture suggests the probability of occurrence of a sequence of digits d is given by the equation Prob d logio 1 d For example the probability of the sequence of digits 1 2 3 is given by logio 1 123 The frequency of digits can deviate from the law for a range of reasons mostly to do with constraints on possible values. Deviations due to human fabrication or alteration of data have been shown to be useful for detecting fraud in financial data Nig00 . Although Benford s law holds on the first digit of some scientific datasets particularly those covering large orders of magnitude it is clearly not valid for data such as simple time series where the variance is small relative to the mean. As a simple example the data with a mean of 5 and standard deviation of 1 would tend to have leading digits around 4 or 5 rather than one. Despite this it is possible that subsequent digits may conform better. A recent experimental study suggested the second digit was a much more reliable indicator of fabricated experimental data Die04 . Such a relationship would be very useful on time series data as generated by geophysical data. This paper reports some tests of the second digit frequency as a practical methodology for detecting result management in geophysical data. It also illustrates
