| Overview of the JET results in support to ITER X Litaudon, S Abduallev, M Abhangi, P Abreu, M Afzal, KM Aggarwal, ... Nuclear Fusion 57 (10), 102001, 2017 | 207 | 2017 |
| Overview of the JET results with the ITER-like wall F Romanelli, JETE Contributors Nuclear Fusion 53 (10), 104002, 2013 | 177* | 2013 |
| Overview of the JET preparation for deuterium–tritium operation with the ITER like-wall E Joffrin, S Abduallev, M Abhangi, P Abreu, V Afanasev, M Afzal, ... Nuclear Fusion 59 (11), 112021, 2019 | 141 | 2019 |
| Efficient generation of energetic ions in multi-ion plasmas by radio-frequency heating YO Kazakov, J Ongena, JC Wright, SJ Wukitch, E Lerche, MJ Mantsinen, ... Nature Physics 13 (10), 973-978, 2017 | 127 | 2017 |
| Overview of JET results for optimising ITER operation J Mailloux, N Abid, K Abraham, P Abreu, O Adabonyan, P Adrich, ... Nuclear Fusion 62 (4), 042026, 2022 | 116 | 2022 |
| Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model F Felici, J Citrin, AA Teplukhina, J Redondo, C Bourdelle, F Imbeaux, ... Nuclear Fusion 58 (9), 096006, 2018 | 79 | 2018 |
| Clustering based on the geodesic distance on Gaussian manifolds for the automatic classification of disruptions A Murari, P Boutot, J Vega, M Gelfusa, R Moreno, G Verdoolaege, ... Nuclear Fusion 53 (3), 033006, 2013 | 72 | 2013 |
| Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET A Murari, M Lungaroni, E Peluso, P Gaudio, J Vega, S Dormido-Canto, ... Nuclear Fusion 58 (5), 056002, 2018 | 62 | 2018 |
| Disruption prediction with artificial intelligence techniques in tokamak plasmas J Vega, A Murari, S Dormido-Canto, GA Rattá, M Gelfusa Nature Physics 18 (7), 741-750, 2022 | 54 | 2022 |
| W transport and accumulation control in the termination phase of JET H-mode discharges and implications for ITER F Köchl, A Loarte, E De La Luna, V Parail, G Corrigan, D Harting, I Nunes, ... Plasma Physics and Controlled Fusion 60 (7), 074008, 2018 | 50 | 2018 |
| 14 MeV calibration of JET neutron detectors—phase 1: calibration and characterization of the neutron source P Batistoni, S Popovichev, A Cufar, Z Ghani, L Giacomelli, S Jednorog, ... Nuclear Fusion 58 (2), 026012, 2017 | 49 | 2017 |
| High fusion performance at high Ti/Te in JET-ILW baseline plasmas with high NBI heating power and low gas puffing HT Kim, ACC Sips, M Romanelli, CD Challis, F Rimini, L Garzotti, ... Nuclear Fusion 58 (3), 036020, 2018 | 47 | 2018 |
| Upgrading model selection criteria with goodness of fit tests for practical applications R Rossi, A Murari, P Gaudio, M Gelfusa Entropy 22 (4), 447, 2020 | 46 | 2020 |
| Application of a CO2 dial system for infrared detection of forest fire and reduction of false alarm. C Bellecci, M Francucci, P Gaudio, M Gelfusa, S Martellucci, M Richetta, ... Applied Physics B: Lasers & Optics 87 (2), 2007 | 45 | 2007 |
| On the transfer of adaptive predictors between different devices for both mitigation and prevention of disruptions A Murari, R Rossi, E Peluso, M Lungaroni, P Gaudio, M Gelfusa, G Ratta, ... Nuclear fusion 60 (5), 056003, 2020 | 40 | 2020 |
| Application of symbolic regression to the derivation of scaling laws for tokamak energy confinement time in terms of dimensionless quantities A Murari, E Peluso, M Lungaroni, M Gelfusa, P Gaudio Nuclear Fusion 56 (2), 026005, 2015 | 40 | 2015 |
| Adaptive learning for disruption prediction in non-stationary conditions A Murari, M Lungaroni, M Gelfusa, E Peluso, J Vega, JET Contributors Nuclear fusion 59 (8), 086037, 2019 | 37 | 2019 |
| Maximum likelihood bolometric tomography for the determination of the uncertainties in the radiation emission on JET TOKAMAK T Craciunescu, E Peluso, A Murari, M Gelfusa, JET Contributors Review of Scientific Instruments 89 (5), 2018 | 35 | 2018 |
| Two realistic scenarios of intentional release of radionuclides (Cs-137, Sr-90)-the use of the HotSpot code to forecast contamination extent D Di Giovanni, F Marchi, G Latini, M Carestia, A Malizia, M Gelfusa, ... WSEAS Transactions on Environment and Development 10, 106-122, 2014 | 35 | 2014 |
| Symbolic regression via genetic programming for data driven derivation of confinement scaling laws without any assumption on their mathematical form A Murari, E Peluso, M Gelfusa, I Lupelli, M Lungaroni, P Gaudio Plasma Physics and Controlled Fusion 57 (1), 014008, 2014 | 34 | 2014 |