{"paper":{"title":"LinKS: Discovering galaxy-scale strong lenses in the Kilo-Degree Survey using Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.GA","authors_text":"A. Dvornik, A. H. Wright, B. Giblin, C. E. Petrillo, C. Heymans, C. Spiniello, C. Tortora, F. Getman, G. Covone, G. Verdoes Kleijn, G. Vernardos, H. Shan, J. T. A. de Jong, K. Kuijken, L. V. E. Koopmans, M. Bilicki, N. R. Napolitano, P. Schneider, S. Chatterjee, T. Erben","submitted_at":"2018-12-07T18:59:58Z","abstract_excerpt":"We present a new sample of galaxy-scale strong gravitational-lens candidates, selected from 904 square degrees of Data Release 4 of the Kilo-Degree Survey (KiDS), i.e., the \"Lenses in the Kilo-Degree Survey\" (LinKS) sample. We apply two Convolutional Neural Networks (ConvNets) to $\\sim88\\,000$ colour-magnitude selected luminous red galaxies yielding a list of 3500 strong-lens candidates. This list is further down-selected via human inspection. The resulting LinKS sample is composed of 1983 rank-ordered targets classified as \"potential lens candidates\" by at least one inspector. Of these, a hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03168","kind":"arxiv","version":2},"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"}