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We analyzed how often and in what ways the Journal Impact Factor (JIF) is currently used in review, promotion, and tenure (RPT) documents of a representative sample of universities from the United States and Canada. 40% of research-intensive institutions and 18% of master’s institutions mentioned the JIF, or closely related terms. Of the institutions that mentioned the JIF, 87% supported its use in at least one of their RPT documents, 13% expressed caution about its use, and none heavily criticized it or prohibited its use. Furthermore, 63% of institutions that mentioned the JIF associated the metric with quality, 40% with impact, importance, or significance, and 20% with prestige, reputation, or status. We conclude that use of the JIF is encouraged in RPT evaluations, especially at research-intensive universities, and that there is work to be done to avoid the potential misuse of metrics like the JIF.

Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.

Traditionally, the success of a researcher is assessed by the number of publications he or she publishes in peer-reviewed, indexed, high impact journals. This essential yardstick, often referred to as the impact of a specific researcher, is assessed through the use of various metrics. While researchers may be acquainted with such matrices, many do not know how to use them to enhance their careers. In addition to these metrics, a number of other factors should be taken into consideration to objectively evaluate a scientist's profile as a researcher and academician. Moreover, each metric has its own limitations that need to be considered when selecting an appropriate metric for evaluation. This paper provides a broad overview of the wide array of metrics currently in use in academia and research. Popular metrics are discussed and defined, including traditional metrics and article-level metrics, some of which are applied to researchers for a greater understanding of a particular concept, including varicocele that is the thematic area of this Special Issue of Asian Journal of Andrology. We recommend the combined use of quantitative and qualitative evaluation using judiciously selected metrics for a more objective assessment of scholarly output and research impact.

Ambio is a leading journal in environmental science and policy, sustainable development, and human-environment interactions. The paper at hand aims to run a bibliometric analysis to inspect the main publications features of Ambio in Science Citation Index Expanded SCI-EXPANDED. For this scope, a bibliometric survey has been carried out to investigate the journal’s historic characteristics in the Web of Science (WoS) categories of environmental sciences and environmental engineering for Ambio from 1980 to 2019. These are the categories for which the journal has been indexed throughout the indexed time frame. The paper proposes technical and methodological innovations, including improvements in the methods and original characteristics analyzed. Documents published in Ambio were searched out from SCI-EXPANDED. Six publication indicators were applied to evaluate the publication performance of countries, institutes, and authors. Three citation indicators were used to compare publications. As a parameter, the journal impact factor contributor was applied to compare the most frequently cited publications. The journal impact factor contributing publications were also discussed. Results show that Sweden ranked top in six publication indicators and that the top three productive institutes were located in Sweden. A low percentage of productive authors emerged as a journal impact factor contributor. Similarly, a low relationship between the IF contributing publications and the highly cited publications was also found. Less than half of the top 100 highly cited publications in Ambio did not lie within the high impact in most the recent year of 2019. Three members of the advisory board in Ambio were the main productive authors. T.V. Callaghan contributed to most of the publications while papers published by J. Rockstrom as first and corresponding author contributed the most to the journal impact factor. An article authored by Steffen et al. ( 2007 ) scored the highest total citations in 2019.

The lack of predictability of citation-based measures frequently used to gauge impact, from impact factors to short-term citations, raises a fundamental question: Is there long-term predictability in citation patterns? Here, we derive a mechanistic model for the citation dynamics of individual papers, allowing us to collapse the citation histories of papers from different journals and disciplines into a single curve, indicating that all papers tend to follow the same universal temporal pattern. The observed patterns not only help us uncover basic mechanisms that govern scientific impact but also offer reliable measures of influence that may have potential policy implications.

The authors evaluate the quality of research reported in major journals in social-personality psychology by ranking those journals with respect to their N-pact Factors (NF)-the statistical power of the empirical studies they publish to detect typical effect sizes. Power is a particularly important attribute for evaluating research quality because, relative to studies that have low power, studies that have high power are more likely to (a) to provide accurate estimates of effects, (b) to produce literatures with low false positive rates, and (c) to lead to replicable findings. The authors show that the average sample size in social-personality research is 104 and that the power to detect the typical effect size in the field is approximately 50%. Moreover, they show that there is considerable variation among journals in sample sizes and power of the studies they publish, with some journals consistently publishing higher power studies than others. The authors hope that these rankings will be of use to authors who are choosing where to submit their best work, provide hiring and promotion committees with a superior way of quantifying journal quality, and encourage competition among journals to improve their NF rankings.

Research is a highly competitive profession where evaluation plays a central role; journals are ranked and individuals are evaluated based on their publication number, the number of times they are cited and their h-index. Yet such evaluations are often done in inappropriate ways that are damaging to individual careers, particularly for young scholars, and to the profession. Furthermore, as with all indices, people can play games to better their scores. This has resulted in the incentive structure of science increasingly mimicking economic principles, but rather than amonetary gain, the incentive is a higher score. To ensure a diversity of cultural perspectives and individual experiences, we gathered a team of academics in the fields of ecology and evolution from around the world and at different career stages.We first examine how authorship, h-index of individuals and journal impact factors are being used and abused. Second, we speculate on the consequences of the continued use of thesemetrics with the hope of sparking discussions thatwill help our fieldsmove in a positive direction.Wewould like to see changes in the incentive systems, rewarding quality research and guaranteeing transparency. Senior faculty should establish the ethical standards, mentoring practices and institutional evaluation criteria to create the needed changes.

BackgroundUnderstanding the impact of a publication by using bibliometric indices becomes an essential activity not only for universities and research institutes but also for individual academicians. This paper aims to provide a brief review of the current bibliometric tools used by authors and editors and proposes an algorithm to assess the relevance of the most common bibliometric tools to help the researchers select the fittest journal and know the trends of published submissions by using self-evaluation.MethodsWe present a narrative review answering at least two related consecutive questions triggered by the topics mentioned above. How prestigious is a journal based on its most recent bibliometrics, so authors may choose it to submit their next manuscript? And, how can they self-evaluate/understand the impact of their whole publishing scientific life?ResultsWe presented the main relevant definitions of each bibliometrics and grouped them in those oriented to evaluated journals or individuals. Also, we share with our readers our algorithm to assess journals before manuscript submission.ConclusionsSince there is a journal performance market and an article performance market, each one with its patterns, an integrative use of these metrics, rather than just the impact factor alone, might represent the fairest and most legitimate approach to assess the influence and importance of an acceptable research issue, and not only a sound journal in their respective disciplines.

Objective To examine how poor reporting and inadequate methods for key methodological features in randomised controlled trials (RCTs) have changed over the past three decades.Design Mapping of trials included in Cochrane reviews.Data sources Data from RCTs included in all Cochrane reviews published between March 2011 and September 2014 reporting an evaluation of the Cochrane risk of bias items: sequence generation, allocation concealment, blinding, and incomplete outcome data.Data extraction For each RCT, we extracted consensus on risk of bias made by the review authors and identified the primary reference to extract publication year and journal. We matched journal names with Journal Citation Reports to get 2014 impact factors.Main outcomes measures We considered the proportions of trials rated by review authors at unclear and high risk of bias as surrogates for poor reporting and inadequate methods, respectively.Results We analysed 20 920 RCTs (from 2001 reviews) published in 3136 journals. The proportion of trials with unclear risk of bias was 48.7% for sequence generation and 57.5% for allocation concealment; the proportion of those with high risk of bias was 4.0% and 7.2%, respectively. For blinding and incomplete outcome data, 30.6% and 24.7% of trials were at unclear risk and 33.1% and 17.1% were at high risk, respectively. Higher journal impact factor was associated with a lower proportion of trials at unclear or high risk of bias. The proportion of trials at unclear risk of bias decreased over time, especially for sequence generation, which fell from 69.1% in 1986-1990 to 31.2% in 2011-14 and for allocation concealment (70.1% to 44.6%). After excluding trials at unclear risk of bias, use of inadequate methods also decreased over time: from 14.8% to 4.6% for sequence generation and from 32.7% to 11.6% for allocation concealment.Conclusions Poor reporting and inadequate methods have decreased over time, especially for sequence generation and allocation concealment. But more could be done, especially in lower impact factor journals.

The majority of academic papers are scarcely cited while a few others are highly cited. A large number of studies indicate that there are many factors influencing the number of citations. An actual review is missing that provides a comprehensive review of the factors predicting the frequency of citations. In this review, we performed a search in WoS, Scopus, PubMed and Medline to retrieve relevant papers. In overall, 2087 papers were retrieved among which 198 relevant papers were included in the study. Three general categories with twenty eight factors were identified to be related to the number of citations: Category one: “paper related factors”: quality of paper; novelty and interest of subject; characteristics of fields and study topics; methodology; document type; study design; characteristics of results and discussion; use of figures and appendix in papers; characteristics of the titles and abstracts; characteristics of references; length of paper; age of paper; early citation and speed of citation; accessibility and visibility of papers. Category two: “journal related factors”: journal impact factor; language of journal; scope of journal; form of publication. Category three: “author(s) related factors”: number of authors; author’s reputation; author’s academic rank; self-citations; international and national collaboration of authors; authors’ country; gender, age and race of authors; author’s productivity; organizational features; and funding. Probably some factors such as the quality of the paper, journal impact factor, number of authors, visibility and international cooperation are stronger predictors for citations, than authors’ gender, age and race; characteristics of results and discussion and so on.