Marcel Binz
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- General Decision Sciences top 10%
Papers in
-
- Machine Learning and Data Classification 2
- Explainable Artificial Intelligence (XAI) 2
- Topic Modeling 2
- Cognitive Science and Mapping 1
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- Clinical Reasoning and Diagnostic Skills 2
- Co-authors
- Eric R. Schulz (7 shared papers)Dirk U. Wulff (2 shared papers)Rui Mata (1 shared paper)Matthew Botvinick (3 shared papers)Dominik Endres (2 shared papers)Samuel J. Gershman (2 shared papers)Jane X. Wang (2 shared papers)Ishita Dasgupta (2 shared papers)
- Journals
- Behavioral and Brain Sciences (2 papers)Proceedings of the National Academy of Sciences (2 papers)Computational Brain & Behavior (1 paper)Nature (1 paper)Behavior Research Methods (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Marcel Binz
10 papers receiving 438 citations
Marcel Binz's Hit Papers
Peers
Comparison fields: 5 of 75
- Health Informatics 34
- General Decision Sciences 19
- General Social Sciences 20
- Artificial Intelligence 187
- Experimental and Cognitive Psychology 46
Countries citing papers authored by Marcel Binz
This map shows the geographic impact of Marcel Binz'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 Marcel Binz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel Binz more than expected).
Fields of papers citing papers by Marcel Binz
This network shows the impact of papers produced by Marcel Binz. 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 Marcel Binz. The network helps show where Marcel Binz may publish in the future.
Co-authors
The 20 scholars most cited alongside Marcel Binz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Using cognitive psychology to understand GPT-3 Hit paper breakdown → | 2023 | 306 |
| 2 | A foundation model to predict and capture human cognition Hit paper breakdown → | 2025 | 37 |
| 3 | 2024 | 33 | |
| 4 | 2025 | 27 | |
| 5 | 2023 | 21 | |
| 6 | 2022 | 12 | |
| 7 | 2022 | 7 | |
| 8 | Where Do Heuristics Come From | 2019 | 4 |
| 9 | 2024 | 3 | |
| 10 | 2022 | 1 |
About Marcel Binz
Marcel Binz is a scholar working on Artificial Intelligence, Family Practice, General Decision Sciences, General Social Sciences and Social Psychology, having authored 10 papers that have together received 451 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers), Computational and Text Analysis Methods (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Decision-Making and Behavioral Economics (2 papers), Topic Modeling (2 papers), Neural and Behavioral Psychology Studies (1 paper) and Cognitive Science and Mapping (1 paper). The work is most often cited by research in Health Informatics (34 citations), General Decision Sciences (19 citations), General Social Sciences (20 citations), Artificial Intelligence (187 citations) and Experimental and Cognitive Psychology (46 citations). Marcel Binz has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Eric R. Schulz, Dirk U. Wulff, Rui Mata, Matthew Botvinick, Dominik Endres, Samuel J. Gershman, Jane X. Wang, Ishita Dasgupta, Marco Marelli and Adina L. Roskies. Their work appears in journals such as Behavioral and Brain Sciences, Proceedings of the National Academy of Sciences, Computational Brain & Behavior, Nature and Behavior Research Methods.
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.