{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6A65AB3EKM5CVSW5PST7B2TKZK","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":"41be1ed69ea8df89f942ddc1f3e44c573bb9c6c969bcef4960f2fa40ce5d73ef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-24T18:30:26Z","title_canon_sha256":"e31b55c8734c69ebd8219aee08d7afcad4878b79d48131f320b6cd792ad4635a"},"schema_version":"1.0","source":{"id":"2206.12458","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.12458","created_at":"2026-07-05T05:50:43Z"},{"alias_kind":"arxiv_version","alias_value":"2206.12458v3","created_at":"2026-07-05T05:50:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.12458","created_at":"2026-07-05T05:50:43Z"},{"alias_kind":"pith_short_12","alias_value":"6A65AB3EKM5C","created_at":"2026-07-05T05:50:43Z"},{"alias_kind":"pith_short_16","alias_value":"6A65AB3EKM5CVSW5","created_at":"2026-07-05T05:50:43Z"},{"alias_kind":"pith_short_8","alias_value":"6A65AB3E","created_at":"2026-07-05T05:50:43Z"}],"graph_snapshots":[{"event_id":"sha256:e1e4d6a8afc3928d062f7da944f2086492900580b44d1dcf31d8d26c7ddd7d54","target":"graph","created_at":"2026-07-05T05:50:43Z","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/2206.12458/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Camera traps are a method for monitoring wildlife and they collect a large number of pictures. The number of images collected of each species usually follows a long-tail distribution, i.e., a few classes have a large number of instances, while a lot of species have just a small percentage. Although in most cases these rare species are the ones of interest to ecologists, they are often neglected when using deep-learning models because these models require a large number of images for the training. In this work, a simple and effective framework called Square-Root Sampling Branch (SSB) is propose","authors_text":"Eulanda M. dos Santos, Fagner Cunha, Juan G. Colonna","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-24T18:30:26Z","title":"Bag of Tricks for Long-Tail Visual Recognition of Animal Species in Camera-Trap Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.12458","kind":"arxiv","version":3},"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":"sha256:3635b7ddaaea6dbd90daac33b21613fecc24913eaaad922efe9afc6a8e3c6b00","target":"record","created_at":"2026-07-05T05:50:43Z","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":"41be1ed69ea8df89f942ddc1f3e44c573bb9c6c969bcef4960f2fa40ce5d73ef","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-06-24T18:30:26Z","title_canon_sha256":"e31b55c8734c69ebd8219aee08d7afcad4878b79d48131f320b6cd792ad4635a"},"schema_version":"1.0","source":{"id":"2206.12458","kind":"arxiv","version":3}},"canonical_sha256":"f03dd00764533a2acadd7ca7f0ea6aca9b3a6aba44419ed9f27bd4b773bc9da2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f03dd00764533a2acadd7ca7f0ea6aca9b3a6aba44419ed9f27bd4b773bc9da2","first_computed_at":"2026-07-05T05:50:43.155793Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:50:43.155793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pEtD9S9Uh4IDs4yFauUKDqNodRODpdnAJRUnmwUoBOeWWR/LErqP/SkEaBQnn7UcifBSAnYYGw0kWLJYMpdKCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:50:43.156341Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.12458","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3635b7ddaaea6dbd90daac33b21613fecc24913eaaad922efe9afc6a8e3c6b00","sha256:e1e4d6a8afc3928d062f7da944f2086492900580b44d1dcf31d8d26c7ddd7d54"],"state_sha256":"0db743aadba9b2cf566bad503884e229d17e4a00b60b432bbd3d09c55b6e1cbe"}