The academic publishing world is changing significantly, with ever-growing numbers of publications each year and shifting publishing patterns. However, the metrics used to measure academic success, such as the number of publications, citation number, and impact factor, have not changed for decades. Moreover, recent studies indicate that these metrics have become targets and follow Goodhart's Law, according to which "when a measure becomes a target, it ceases to be a good measure." In this study, we analyzed over 120 million papers to examine how the academic publishing world has evolved over the last century. Our study shows that the validity of citation-based measures is being compromised and their usefulness is lessening. In particular, the number of publications has ceased to be a good metric as a result of longer author lists, shorter papers, and surging publication numbers. Citation-based metrics, such citation number and h-index, are likewise affected by the flood of papers, self-citations, and lengthy reference lists. Measures such as a journal's impact factor have also ceased to be good metrics due to the soaring numbers of papers that are published in top journals, particularly from the same pool of authors. Moreover, by analyzing properties of over 2600 research fields, we observed that citation-based metrics are not beneficial for comparing researchers in different fields, or even in the same department. Academic publishing has changed considerably; now we need to reconsider how we measure success.
One of the best-known and most-used measures to evaluate journals' importance is the impact factor, devised over 60 years ago by Eugene Garfield @cite_28 . The impact factor measures the frequency in which an average article in a journal has been cited in a specific year. Over time, the measure has been used to evaluate institutions, scientific research, entire journals, and individual articles'' @cite_26 . Another common metric to measure a researcher's output or a journal's impact is the h-index, which measures an author's or a journal's number of papers that have at least h citations each @cite_21 . It has been shown that the h-index can predict academic achievements @cite_43 .
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A piece of material (part) having a preformed cross-sectional configuration is moved through a pair of pinch rolls located in between right and left hand forming rolls. Each forming roll is position adjustable both laterally and separationwise with respect to the pinch rolls along two longitudinal axes. In addition, each forming roll is rotationally adjustable along two rotational axes. As the part moves through the machine, the right and left hand forming rolls are positioned in accordance with a numerical program. The positioning is such that the piece of material is uniplanar or multiplanar contoured in a desired manner. As the contoured part exits from the machine, it passes through a uniplanar or a multiplanar sensor, which senses the contour of the part, including any springback occurring subsequent to roll forming. The sensed information is used to adaptively modify the control signals controlling the position of the right and left hand forming rolls. The signal output(s) of the uniplanar or multiplanar sensor is (are) integrated to improve its (their) stability. The integrated signal(s) are used to develop correction signals (k) for each controllable longitudinal or rotational axis in accordance with the following algorithm q0 k = k0 + - 1 q1 WHERE: K0 EQUALS THE PRECEDING CORRECTION FACTOR; Q0 EQUALS THE CONTOUR REFERENCE VALUE COMPUTED FROM PART GEOMETRY AND SUPPLIED BY THE NUMERICAL CONTROL SIGNAL SOURCE; AND, Q1 EQUALS THE CONTOUR MEASUREMENT SENSED BY THE SENSOR ALONG THE AXIS WHOSE CORRECTION FACTOR IS BEING COMPUTED. The axis control signals are multiplied by the thusly developed axis correction signals to provide corrected axis control signals which are utilized to control the movement of the forming rolls along their respective longitudinal and rotational axes. Bibliometric measures of individual scientific achievement are of particular interest if they can be used to predict future achievement. Here we report results of an empirical study of the predictive power of the h index compared with other indicators. Our findings indicate that the h index is better than other indicators considered (total citation count, citations per paper, and total paper count) in predicting future scientific achievement. We discuss reasons for the superiority of the h index. I propose the index h, defined as the number of papers with citation number ≥h, as a useful index to characterize the scientific output of a researcher.