C. Baldanza

940 citations
11 papers · 32 · h-index 5

Impact in

Papers in

C. Baldanza

10 papers receiving 30 citations

Peers

C. Baldanza
Comparison fields: 5 of 17
  • Nuclear and High Energy Physics 20
  • Radiation 6
  • Artificial Intelligence 18
  • Hardware and Architecture 3
  • Instrumentation 1
Replace M. Lolli with:
M. Lolli Italy
M. Campbell United States
J. Gläß Germany
A. Wegner Germany
G. Prior Switzerland
K. Maeshima United States
D. Goldner Germany
W. Fröchtenicht Germany
T. Krämerkämper Germany
F. Tegenfeldt Switzerland
C. Baldanza relative to M. Lolli Italy M. Lolli's profile →
Citations per field
00.5×
M. Lolli · 1×
Citations per year

Countries citing papers authored by C. Baldanza

Since Specialization
Citations

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

Fields of papers citing papers by C. Baldanza

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside C. Baldanza, 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 C. Baldanza Line = papers co-authored together C. Baldanza links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 19957
2 19954
3 20024
4 20164
5 19964
6 20223
7 20172
8 19962
9 20231
10
Results from an on-line neural trigger within a fixed target experiment for the production of beauty particles
19931
11 20190

About C. Baldanza

C. Baldanza is a scholar working on Nuclear and High Energy Physics, Radiation, Artificial Intelligence, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 11 papers that have together received 32 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (7 papers), Neural Networks and Applications (4 papers), Radiation Detection and Scintillator Technologies (4 papers), Neutrino Physics Research (2 papers), Advanced Data Storage Technologies (2 papers), Neural Networks Stability and Synchronization (1 paper), Statistical Mechanics and Entropy (1 paper) and Atomic and Subatomic Physics Research (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (20 citations), Radiation (6 citations), Artificial Intelligence (18 citations), Hardware and Architecture (3 citations) and Instrumentation (1 citation). C. Baldanza has collaborated with scholars based in Italy, Germany and Switzerland. Frequent co-authors include M Zuffa, I. DʼAntone, Claudio Bruschini, F. Odorici, P. Mazzanti, Maurizio Bruschi, R. Odorico, María Rízzí, M. Passaseo and L. Malferrari. Their work appears in journals such as Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment, IEEE Transactions on Nuclear Science, International Journal of Modern Physics C and CERN Document Server (European Organization for Nuclear Research).

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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