{"paper":{"title":"Search for gamma-ray-emitting active galactic nuclei in the Fermi-LAT unassociated sample using machine learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","physics.data-an"],"primary_cat":"astro-ph.HE","authors_text":"M. Doert, M. Errando","submitted_at":"2013-12-19T20:24:53Z","abstract_excerpt":"The second Fermi-LAT source catalog (2FGL) is the deepest all-sky survey available in the gamma-ray band. It contains 1873 sources, of which 576 remain unassociated. Machine-learning algorithms can be trained on the gamma-ray properties of known active galactic nuclei (AGN) to find objects with AGN-like properties in the unassociated sample. This analysis finds 231 high-confidence AGN candidates, with increased robustness provided by intersecting two complementary algorithms. A method to estimate the performance of the classification algorithm is also presented, that takes into account the dif"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.5726","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}