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| 4FGL J1439.5-2525 , the SIMBAD biblio (20 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST00:42:32 |
| Bibcode/DOI | Score |
in Title|Abstract| Keywords |
in a table | in teXt, Caption, ... | Nb occurence | Nb objects in ref |
Citations (from ADS) |
Title | First 3 Authors |
|---|---|---|---|---|---|---|---|---|---|
|
2017ApJS..232...18A |
16 | D | 1584 | 263 | 3FHL: the Third Catalog of Hard Fermi-LAT Sources. | AJELLO M., ATWOOD W.B., BALDINI L., et al. | |||
|
2018ApJS..237...32A |
16 | D | 1 | 2605 | 130 | The search for spatial extension in high-latitude sources detected by the Fermi Large Area Telescope. | ACKERMANN M., AJELLO M., BALDINI L., et al. | ||
|
2018A&A...619A..23C |
16 | D | 1 | 1351 | ~ | A MST catalogue of γ-ray source candidates above 10 GeV and at Galactic latitudes higher than 20°. | CAMPANA R., MASSARO E. and BERNIERI E. | ||
| 2019ApJS..241....5D | 97 | D | X | 3 | 29 | ~ | Identifying the 3FHL catalog. III. Results of the CTIO-COSMOS optical spectroscopy campaign. | DESAI A., MARCHESI S., RAJAGOPAL M., et al. | |
|
2019ApJ...887..134K |
16 | D | 1 | 1314 | ~ | Evaluating the classification of Fermi BCUs from the 4FGL catalog using machine learning. | KANG S.-J., LI E., OU W., et al. | ||
|
2020MNRAS.493.1926K |
16 | D | 1 | 1330 | ~ | Classification of blazar candidates of uncertain type from the Fermi LAT 8-yr source catalogue with an artificial neural network. | KOVACEVIC M., CHIARO G., CUTINI S., et al. | ||
|
2020ApJS..247...33A |
16 | D | 1 | 5175 | 880 | Fermi Large Area Telescope fourth source catalog. | ABDOLLAHI S., ACERO F., ACKERMANN M., et al. | ||
|
2020ApJ...892..105A |
16 | D | 1 | 3421 | 235 | The fourth catalog of active galactic nuclei detected by the Fermi Large Area Telescope. | AJELLO M., ANGIONI R., AXELSSON M., et al. | ||
|
2021ApJS..253...46P |
17 | D | 1 | 1078 | 38 | The central engines of Fermi blazars. | PALIYA V.S., DOMINGUEZ A., AJELLO M., et al. | ||
| 2021MNRAS.504.3338P | 17 | D | 2 | 99 | ~ | The spectra of IceCube neutrino candidate sources - I. Optical spectroscopy of blazars. | PAIANO S., FALOMO R., TREVES A., et al. | ||
| 2021MNRAS.505.5853G | 17 | D | 2 | 5834 | ~ | Artificial Neural Network classification of 4FGL sources. | GERMANI S., TOSTI G., LUBRANO P., et al. | ||
| 2022MNRAS.510.2671P | 17 | D | 3 | 69 | 12 | The spectra of IceCube neutrino (SIN) candidate sources - II. Source characterization. | PADOVANI P., GIOMMI P., FALOMO R., et al. | ||
|
2022A&A...660A..87B |
17 | D | 1 | 6191 | 10 | Machine learning methods for constructing probabilistic Fermi-LAT catalogs. | BHAT A. and MALYSHEV D. | ||
|
2022ApJS..260...53A |
17 | D | 1 | 6710 | 133 | Incremental Fermi Large Area Telescope Fourth Source Catalog. | ABDOLLAHI S., ACERO F., BALDINI L., et al. | ||
|
2022ApJ...934..180K |
17 | D | 1 | 80 | 8 | Multiwavelength Search for the Origin of IceCube's Neutrinos. | KUN E., BARTOS I., BECKER TJUS J., et al. | ||
|
2022ApJS..263...24A |
17 | D | 1 | 3828 | 15 | The Fourth Catalog of Active Galactic Nuclei Detected by the Fermi Large Area Telescope: Data Release 3. | AJELLO M., BALDINI L., BALLET J., et al. | ||
| 2023MNRAS.521.2270P | 627 | D | S X F | 13 | 62 | ~ | The spectra of IceCube Neutrino (SIN) candidate sources - III. Optical spectroscopy and source characterization of the full sample. | PAIANO S., FALOMO R., TREVES A., et al. | |
| 2023MNRAS.523.4120D | 17 | D | 1 | 420 | ~ | Hybrid deep learning for blazar classification and correlation search with neutrinos. | DING J., HUANG Y., LI X.-D., et al. | ||
| 2023MNRAS.526..661K | 17 | D | 2 | 55 | ~ | The spectra of IceCube Neutrino (SIN) candidate sources - IV. Spectral energy distributions and multiwavelength variability. | KARL M., PADOVANI P. and GIOMMI P. | ||
| 2023A&A...679A..46K | 17 | D | 1 | 37 | ~ | Searching for temporary gamma-ray dark blazars associated with IceCube neutrinos. | KUN E., BARTOS I., BECKER TJUS J., et al. |