Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models

1.4k indexed citations
published 2004

Countries where authors are citing Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models

Specialization
Citations

This map shows the geographic impact of Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models more than expected).

Fields of papers citing Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models.

About Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models

This paper, published in 2004, received 1.4k indexed citations . Written by Andrea Saltelli, Stefano Tarantola, Francesca Campolongo and Marco Ratto. It is primarily cited by scholars working on Statistics, Probability and Uncertainty (396 citations), Environmental Engineering (282 citations) and Civil and Structural Engineering (202 citations).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/w3506596.

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