{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:T4XHMNVDAHXFWYHB2WYXQPVCJN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8780f3c7d245729f0023b96864a6355051fa8b5833fe77db0c48e07c9bb2aef6","cross_cats_sorted":["astro-ph.HE","astro-ph.IM","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2023-02-03T19:00:51Z","title_canon_sha256":"b46761e2fc2c3d534caecdf691a81c9f2dde9bbd0c3e6485a7bdf3319c083024"},"schema_version":"1.0","source":{"id":"2302.01947","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.01947","created_at":"2026-07-05T08:19:18Z"},{"alias_kind":"arxiv_version","alias_value":"2302.01947v2","created_at":"2026-07-05T08:19:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.01947","created_at":"2026-07-05T08:19:18Z"},{"alias_kind":"pith_short_12","alias_value":"T4XHMNVDAHXF","created_at":"2026-07-05T08:19:18Z"},{"alias_kind":"pith_short_16","alias_value":"T4XHMNVDAHXFWYHB","created_at":"2026-07-05T08:19:18Z"},{"alias_kind":"pith_short_8","alias_value":"T4XHMNVD","created_at":"2026-07-05T08:19:18Z"}],"graph_snapshots":[{"event_id":"sha256:5a1301471e0eba8fd7994a41e154dcaa3749b9795fc84b1eb084aa8a7a3eeeac","target":"graph","created_at":"2026-07-05T08:19:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2302.01947/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We reconstruct the extra-galactic gamma-ray source-count distribution, or $dN/dS$, of resolved and unresolved sources by adopting machine learning techniques. Specifically, we train a convolutional neural network on synthetic 2-dimensional sky-maps, which are built by varying parameters of underlying source-counts models and incorporate the Fermi-LAT instrumental response functions. The trained neural network is then applied to the Fermi-LAT data, from which we estimate the source count distribution down to flux levels a factor of 50 below the Fermi-LAT threshold. We perform our analysis using","authors_text":"Alessandro Cuoco, Aurelio Amerio, Nicolao Fornengo","cross_cats":["astro-ph.HE","astro-ph.IM","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2023-02-03T19:00:51Z","title":"Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.01947","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4177a4d832ae38d374d8c52701802c363c4cfcd009141e1434893bea991e5a62","target":"record","created_at":"2026-07-05T08:19:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8780f3c7d245729f0023b96864a6355051fa8b5833fe77db0c48e07c9bb2aef6","cross_cats_sorted":["astro-ph.HE","astro-ph.IM","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2023-02-03T19:00:51Z","title_canon_sha256":"b46761e2fc2c3d534caecdf691a81c9f2dde9bbd0c3e6485a7bdf3319c083024"},"schema_version":"1.0","source":{"id":"2302.01947","kind":"arxiv","version":2}},"canonical_sha256":"9f2e7636a301ee5b60e1d5b1783ea24b6a7d14b66f48dc385b6f37caddec8311","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f2e7636a301ee5b60e1d5b1783ea24b6a7d14b66f48dc385b6f37caddec8311","first_computed_at":"2026-07-05T08:19:18.147204Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:19:18.147204Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/WWqO0W6FHAl0bA55fHYrnvWpi1UB76KAaM1Sc/rad0ZsRiDhMpEW1UJFbnfQRSipptmBQbIGH+adpnii1eWDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:19:18.147770Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.01947","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4177a4d832ae38d374d8c52701802c363c4cfcd009141e1434893bea991e5a62","sha256:5a1301471e0eba8fd7994a41e154dcaa3749b9795fc84b1eb084aa8a7a3eeeac"],"state_sha256":"9782a3c8ff73ebc7b5341f90bb11d3b4b7c225fc2d62e58d8ddbb6117e7faab6"}