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| RX J0830.1+5230 , the SIMBAD biblio (19 results) | C.D.S. - SIMBAD4 rel 1.8 - 2026.10.18CEST23:55:09 |
| 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 |
|---|---|---|---|---|---|---|---|---|---|
|
2003A&A...406..535Z |
15 | D | 1 | 10257 | 80 | The Hamburg/RASS Catalogue of optical identifications. Northern high-galactic latitude ROSAT Bright Source Catalogue X-ray sources. | ZICKGRAF F.-J., ENGELS D., HAGEN H.-J., et al. | ||
|
2009ApJS..184..138H |
15 | D | 1 | 20623 | 68 | XID II: statistical cross-association of ROSAT bright source catalog X-ray sources with 2MASS point source catalog near-infrared sources. | HAAKONSEN C.B. and RUTLEDGE R.E. | ||
|
2017A&A...598A..17C |
16 | D | 1 | 1692 | 30 | 2WHSP: A multi-frequency selected catalogue of high energy and very high energy γ-ray blazars and blazar candidates. | CHANG Y.-L., ARSIOLI B., GIOMMI P., 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. | ||
|
2021ApJS..253...46P |
17 | D | 1 | 1078 | 38 | The central engines of Fermi blazars. | PALIYA V.S., DOMINGUEZ A., AJELLO M., et al. | ||
|
2021ApJ...913..120Z |
17 | D | 1 | 1126 | ~ | Cosmological evolution of Fermi Large Area Telescope gamma-ray blazars using novel nonparametric methods. | ZENG H., PETROSIAN V. and YI T. | ||
| 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. | ||
|
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..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. | ||
| 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. | ||
|
2023ApJS..268...23F |
17 | D | 1 | 2708 | ~ | Characterizing the Emission Region Properties of Blazars. | FAN J., XIAO H., YANG W., et al. | ||
| 2024ApJ...967..104Z | 18 | D | 4 | 372 | ~ | The Energy Budget in the Jet of High-frequency Peaked BL Lacertae Objects. | ZHAO X.Z., YANG H.Y., ZHENG Y.G., et al. |