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| 3FGL J0539.2-0536 , the SIMBAD biblio (14 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.17CEST05:02:42 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
2015ApJS..218...23A |
16 | D | 1 | 3140 | 1411 | Fermi Large Area Telescope third source catalog. | ACERO F., ACKERMANN M., AJELLO M., et al. | ||
|
2016ApJ...820....8S |
16 | D | 1 | 3047 | 91 | Classification and ranking of Fermi LAT gamma-ray sources from the 3FGL catalog using machine learning techniques. | SAZ PARKINSON P.M., XU H., YU P.L.H., et al. | ||
| 2016RAA....16f..12D | 16 | D | 1 | 44 | ~ | Identification of candidate millisecond pulsars from Fermi LAT observations. | DAI X.-J., WANG Z.-X., VADAKKUMTHANI J., et al. | ||
| 2016A&A...591A..71M | 79 | C | 1 | 43 | 3 | Embedded star clusters as sources of high-energy cosmic rays Modelling and constraints. | MAURIN G., MARCOWITH A., KOMIN N., et al. | ||
| 2021MNRAS.505.5853G | 17 | D | 1 | 5834 | ~ | Artificial Neural Network classification of 4FGL sources. | GERMANI S., TOSTI G., LUBRANO P., et al. | ||
|
2022A&A...660A..87B |
17 | D | 2 | 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..262...18Y |
17 | D | 1 | 2709 | 8 | The Spectral Energy Distributions for 4FGL Blazars. | YANG J.H., FAN J.H., LIU Y., 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. | ||
|
2023ApJS..268...23F |
17 | D | 1 | 2708 | ~ | Characterizing the Emission Region Properties of Blazars. | FAN J., XIAO H., YANG W., 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. | |||||
| 2025A&A...694A..46A | 47 | X | 1 | 33 | ~ | Continuation of an optical spectroscopic campaign of Fermi blazar candidates with TNG: Discovery of a new changing-look blazar. | ALVAREZ CRESPO N., DOMINGUEZ A., PALIYA V.S., et al. | ||
| 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. | ||
| 2025ApJS..281...53G | 47 | X | 1 | 38 | ~ | 1FLAT: A Firmamento-based Catalog of Active Galactic Nuclei in Fermi-LAT High-Galactic-latitude γ-Ray Sources. | GIOMMI P., DORO M., GOUVEA M., et al. |