Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study
2017790 citationsAiden Doherty, Dan Jackson et al.PLoS ONEprofile →
Author Peers
Peers are selected by citation overlap in the author's most active subfields.
citations ·
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This map shows the geographic impact of Nils Hammerla'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 Nils Hammerla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nils Hammerla more than expected).
This network shows the impact of papers produced by Nils Hammerla. 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 Nils Hammerla. The network helps show where Nils Hammerla may publish in the future.
Co-authorship network of co-authors of Nils Hammerla
This figure shows the co-authorship network connecting the top 25 collaborators of Nils Hammerla.
A scholar is included among the top collaborators of Nils Hammerla 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 Nils Hammerla. Nils Hammerla is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Jurić, Damir, et al.. (2021). Towards more patient friendly clinical notes through language models and ontologies.. PubMed. 2021. 881–890.3 indexed citations
Smith, Samuel, et al.. (2018). Decoding Decoders: Finding Optimal Representation Spaces for Unsupervised Similarity Tasks. arXiv (Cornell University).2 indexed citations
4.
Doherty, Aiden, Dan Jackson, Nils Hammerla, et al.. (2017). Large Scale Population Assessment of Physical Activity Using Wrist Worn Accelerometers: The UK Biobank Study. PLoS ONE. 12(2). e0169649–e0169649.790 indexed citations breakdown →
Kharrufa, Ahmed, Jonathan Hook, Gavin Wood, et al.. (2016). Expressy. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 2832–2844.27 indexed citations
Scherr, Johannes, Luis Roalter, Stefan Diewald, et al.. (2011). GymSkill: Mobile Exercise Skill Assessment to Support Personal Health and Fitness.7 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.