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.
ChatGPT: Jack of all trades, master of none
2023373 citationsJan Kocoń, Igor Cichecki et al.Information Fusionprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Joanna Baran'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 Joanna Baran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joanna Baran more than expected).
This network shows the impact of papers produced by Joanna Baran. 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 Joanna Baran. The network helps show where Joanna Baran may publish in the future.
Co-authorship network of co-authors of Joanna Baran
This figure shows the co-authorship network connecting the top 25 collaborators of Joanna Baran.
A scholar is included among the top collaborators of Joanna Baran 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 Joanna Baran. Joanna Baran 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.
Kocoń, Jan, Igor Cichecki, Oliwier Kaszyca, et al.. (2023). ChatGPT: Jack of all trades, master of none. Information Fusion. 99. 101861–101861.373 indexed citations breakdown →
2.
Lenort, Radim, et al.. (2019). Economic and Environmental Efficiency of the Chemical Industry in Europe in 2010-2016. Rocznik Ochrona Środowiska.5 indexed citations
Baran, Joanna, et al.. (2016). Efficiency of Polish metallurgical industry based on data envelopment analysis. Metalurgija. 55(2). 245–248.4 indexed citations
Baran, Joanna. (2014). Changes in the productivity of agriculture after Polish accession to the European Union. Acta Scientiarum Polonorum. Oeconomia. 13(3).2 indexed citations
7.
Wicki, Ludwik, Bogdan Klepacki, Joanna Baran, et al.. (2014). Systemy logistyczne w funkcjonowaniu przedsiębiorstw przetwórstwa rolno-spożywczego. CeON Repository (Centre for Evaluation in Education and Science).11 indexed citations
Baran, Joanna. (2013). Benchmarking portów morskich bazujący na metodzie Data Envelopment Analysis. Prace Naukowe Politechniki Warszawskiej. Transport.
10.
Baran, Joanna. (2013). Efficiency of the production scale of Polish dairy companies based on Data Envelopment Analysis. Acta Scientiarum Polonorum. Oeconomia. 12(2).9 indexed citations
11.
Baran, Joanna. (2013). Zastosowanie metody AHP do tworzenia rankingu województw według zaawansowania rozwoju transportu. Roczniki Naukowe Stowarzyszenia Ekonomistów Rolnictwa i Agrobiznesu. 15(6). 16–21.
12.
Baran, Joanna, et al.. (2012). Organizacja łańcucha dostaw w branży odzieżowej. Logistyka.2 indexed citations
13.
Baran, Joanna, et al.. (2011). Rozwiązania w zakresie sterowania zapasami w wybranych branżach agrobiznesu. Logistyka.1 indexed citations
Baran, Joanna, et al.. (2010). Skala działalności przedsiębiorstw przetwórstwa rolno-spożywczego a rozwiązania w zakresie gospodarowania zapasami. Logistyka.1 indexed citations
16.
Baran, Joanna, et al.. (2010). Zakres i rola logistyki w przedsiebiorstwach mleczarskich. Wieś Jutra. 1(1). 43–47.3 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.