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| PSO J058.8053-18.7190 , the SIMBAD biblio (17 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST23:00:07 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
2014ApJS..213....3M |
15 | D | 1 | 28362 | 27 | The Low-frequency Radio Catalog of flat-spectrum sources. | MASSARO F., GIROLETTI M., D'ABRUSCO R., et al. | ||
|
2019ApJS..242....4D |
16 | D | 1 | 9583 | 45 | Two new catalogs of blazar candidates in the WISE Infrared sky. | D'ABRUSCO R., ALVAREZ CRESPO N., MASSARO F., et al. | ||
|
2019A&A...632A..77C |
16 | D | 1 | 2017 | 54 | The 3HSP catalogue of extreme and high-synchrotron peaked blazars. | CHANG Y.-L., ARSIOLI B., GIOMMI P., 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. | ||
|
2020ApJS..248...23D |
16 | D | 1 | 283 | ~ | On the physical association of Fermi-LAT blazars with their low-energy counterparts. | DE MENEZES R., D'ABRUSCO R., MASSARO F., et al. | ||
| 2021MNRAS.505.5853G | 17 | D | 2 | 5834 | ~ | Artificial Neural Network classification of 4FGL sources. | GERMANI S., TOSTI G., LUBRANO P., et al. | ||
| 2021AJ....162..177P | 17 | D | 6 | 64 | 5 | Optical spectroscopic observations of gamma-ray blazar Candidates. XI. Optical observations from SOAR, blanco, NTT and OAN-SPM. The story so far. | PENA-HERAZO H.A., PAGGI A., GARCIA-PEREZ A., et al. | ||
|
2021A&A...655A..17S |
17 | D | 1 | 338578 | 3 | The SPECFIND V3.0 catalog of radio continuum cross-identifications and spectra: Reaching lower frequencies. | STEIN Y., VOLLMER B., BOCH T., 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. | ||
|
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.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. | ||
| 2024MNRAS.530.2282D | 1940 | ~ | Predicting conditional probability distributions of redshifts of Active Galactic Nuclei using Hierarchical Correlation Reconstruction. | DUDA J. and BHATTA G. | |||||
| 2025PASP..137f4105D | 19 | D | 1 | 290 | ~ | Improved Fermi Blazar Candidate Classifications with SRG/eROSITA X-Ray Counterparts Using Machine Learning. | DING J. and RODRIGUEZ A.C. |