Auste Simkute

428 citations
10 papers · 191 · 1 hit paper · h-index 6

Impact in

Papers in

Auste Simkute

9 papers receiving 187 citations

Auste Simkute's Hit Papers

The Metacognitive Demands and Opportunities of Generative AI 2024 · 101 citations
1010+1Years since publication255075100

Peers

Auste Simkute
Comparison fields: 5 of 49
  • Health Informatics 21
  • Safety Research 37
  • Computer Science Applications 17
  • Human-Computer Interaction 17
  • Information Systems and Management 21
Replace Ava Elizabeth Scott with:
Ava Elizabeth Scott United Kingdom
Aaron Donsbach United States
Geoff Musick United States
Jaimie Drozdal United States
Sangho Suh Canada
Fiona Draxler Germany
Madeleine Grunde-McLaughlin United States
Wen Duan United States
Matthew Jörke United States
Auste Simkute relative to Ava Elizabeth Scott United Kingdom Ava Elizabeth Scott's profile →
Citations per field
00.5×12×
Ava Elizabeth Scott · 1×
Citations per year

Countries citing papers authored by Auste Simkute

Since Specialization
Citations

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

Fields of papers citing papers by Auste Simkute

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Auste Simkute. 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 Auste Simkute. The network helps show where Auste Simkute may publish in the future.

Co-authors

The 17 scholars most cited alongside Auste Simkute, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Auste Simkute Line = papers co-authored together Auste Simkute links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
The Metacognitive Demands and Opportunities of Generative AI
Hit paper breakdown →
2024101
2 202425
3 202125
4 201914
5 202411
6 20227
7 20204
8 20243
9 20251
10 20240

About Auste Simkute

Auste Simkute is a scholar working on Artificial Intelligence, Information Systems and Management, Safety Research, Social Psychology and Sociology and Political Science, having authored 10 papers that have together received 191 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (5 papers), Ethics and Social Impacts of AI (4 papers), Human-Automation Interaction and Safety (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Scientific Computing and Data Management (2 papers), Personal Information Management and User Behavior (2 papers), Digital Games and Media (2 papers) and Categorization, perception, and language (1 paper). The work is most often cited by research in Health Informatics (21 citations), Safety Research (37 citations), Computer Science Applications (17 citations), Human-Computer Interaction (17 citations) and Information Systems and Management (21 citations). Auste Simkute has collaborated with scholars based in United Kingdom, Spain and Qatar. Frequent co-authors include Sean Rintel, Abigail Sellen, Lev Tankelevitch, Ava Elizabeth Scott, Advait Sarkar, Rhianne Jones, Ewa Luger, Michael Evans, Louise H. Phillips and Bronwyn Jones. Their work appears in journals such as Acta Psychologica, International Journal of Human-Computer Interaction, Frontiers in Education, UCL Discovery (University College London) and Edinburgh Research Explorer.

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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