{"paper":{"title":"J-PLUS: Bayesian object classification with a strum of BANNJOS","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["astro-ph.IM","astro-ph.SR"],"primary_cat":"astro-ph.GA","authors_text":"A. del Pino, A. Ederoclite, A. Hern\\'an-Caballero, A.J. Cenarro, A. Lumbreras-Calle, A. Mar\\'in-Franch, C.A. Galarza, C. Hern\\'andez-Monteagudo, C. L\\'opez-Sanjuan, D. Crist\\'obal-Hornillos, F. Jimenez-Esteban, H. Dom\\'inguez-S\\'anchez, H. V\\'azquez Rami\\'o, J.A. Fern\\'andez-Ontiveros, J. Varela, J. Vega-Ferrero, L. Sodr\\'e Jr., M. Moles, M. Quartin, P. Cruz, P.R.T. Coelho, R.A. Dupke, R.E. Angulo, R. von Marttens, V. Marra","submitted_at":"2024-04-25T12:29:04Z","abstract_excerpt":"With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3,192 deg$^2$ and contains 47.4 million objects. However, the classification algorithms currently implemented in its pipeline are deterministic and based solely on the sources morphology. Our goal is classify the sources identified in the J-PLUS DR3 images into stars, quasi-stellar objects (QSOs), and galaxies. For this task, we present BANNJOS, a machine learning pipeline that uses Bayesian neural networks t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.16567","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2404.16567/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"}