Eeva Leinala

857 total citations · 1 hit paper
8 papers, 515 citations indexed

About

Eeva Leinala is a scholar working on Small Animals, Plant Science and Computational Theory and Mathematics. According to data from OpenAlex, Eeva Leinala has authored 8 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Small Animals, 3 papers in Plant Science and 2 papers in Computational Theory and Mathematics. Recurrent topics in Eeva Leinala's work include Animal testing and alternatives (3 papers), Pesticide Exposure and Toxicity (3 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). Eeva Leinala is often cited by papers focused on Animal testing and alternatives (3 papers), Pesticide Exposure and Toxicity (3 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). Eeva Leinala collaborates with scholars based in France, United States and Australia. Eeva Leinala's co-authors include Ann M. Richard, Olof Johansson, Grace Patlewicz, Ian T. Cousins, Wiebke Drost, Koichi Ohno, Zhanyun Wang, Andreas M. Buser, Yuki Sakuratani and Magdalini Sachana and has published in prestigious journals such as Environmental Science & Technology, Life Sciences and Regulatory Toxicology and Pharmacology.

In The Last Decade

Eeva Leinala

7 papers receiving 503 citations

Hit Papers

A New OECD Definition for Per- and Polyfluoroalkyl Substa... 2021 2026 2022 2024 2021 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eeva Leinala France 6 305 285 139 58 46 8 515
Michelle L. Twaroski United States 5 313 1.0× 309 1.1× 107 0.8× 64 1.1× 10 0.2× 6 476
Anne E. Loccisano United States 10 414 1.4× 387 1.4× 58 0.4× 34 0.6× 9 0.2× 18 685
Chuan-Hai Li China 12 346 1.1× 570 2.0× 55 0.4× 37 0.6× 14 0.3× 15 780
Diane L. Nabb United States 16 649 2.1× 817 2.9× 202 1.5× 24 0.4× 30 0.7× 25 1.1k
Kyle Glover United States 10 207 0.7× 212 0.7× 29 0.2× 74 1.3× 11 0.2× 13 477
William J. Fasano United States 11 418 1.4× 402 1.4× 129 0.9× 6 0.1× 30 0.7× 15 644
Fabian C. Fischer Germany 15 192 0.6× 433 1.5× 30 0.2× 72 1.2× 92 2.0× 23 684
Alexander Böhme Germany 13 60 0.2× 205 0.7× 34 0.2× 59 1.0× 26 0.6× 27 559
Charles N. Lowe United States 10 95 0.3× 147 0.5× 29 0.2× 58 1.0× 17 0.4× 17 350
Robert T. Mingoia United States 10 118 0.4× 329 1.2× 45 0.3× 16 0.3× 23 0.5× 14 438

Countries citing papers authored by Eeva Leinala

Since Specialization
Citations

This map shows the geographic impact of Eeva Leinala's research. 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 Eeva Leinala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eeva Leinala more than expected).

Fields of papers citing papers by Eeva Leinala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eeva Leinala. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eeva Leinala. The network helps show where Eeva Leinala may publish in the future.

Co-authorship network of co-authors of Eeva Leinala

This figure shows the co-authorship network connecting the top 25 collaborators of Eeva Leinala. A scholar is included among the top collaborators of Eeva Leinala based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Eeva Leinala. Eeva Leinala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Leinala, Eeva, et al.. (2024). Large scale OECD health valuation study to estimate the economic benefits of chemical regulation. European Journal of Public Health. 34(Supplement_3).
2.
Carnesecchi, Edoardo, Patience Browne, Sofia Batista Leite, et al.. (2023). OECD harmonised template 201: Structuring and reporting mechanistic information to foster the integration of new approach methodologies for hazard and risk assessment of chemicals. Regulatory Toxicology and Pharmacology. 142. 105426–105426. 15 indexed citations
3.
Wang, Zhanyun, Andreas M. Buser, Ian T. Cousins, et al.. (2021). A New OECD Definition for Per- and Polyfluoroalkyl Substances. Environmental Science & Technology. 55(23). 15575–15578. 340 indexed citations breakdown →
4.
Coady, Katie, Patience Browne, Michelle R. Embry, et al.. (2019). When Are Adverse Outcome Pathways and Associated Assays “Fit for Purpose” for Regulatory Decision-Making and Management of Chemicals?. Integrated Environmental Assessment and Management. 15(4). 633–647. 31 indexed citations
5.
Sakuratani, Yuki, et al.. (2018). Integrated Approaches to Testing and Assessment: OECD Activities on the Development and Use of Adverse Outcome Pathways and Case Studies. Basic & Clinical Pharmacology & Toxicology. 123(S5). 20–28. 55 indexed citations
7.
Delrue, Nathalie, Magdalini Sachana, Yuki Sakuratani, et al.. (2016). The Adverse Outcome Pathway Concept: A Basis for Developing Regulatory Decision-making Tools. Alternatives to Laboratory Animals. 44(5). 417–429. 53 indexed citations
8.
Wexler, Philip, et al.. (2015). Health effects of toxicants: Online knowledge support. Life Sciences. 145. 284–293. 5 indexed 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.

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