{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:2XONVLZNCAZYPAEJC7QUK3M5AX","short_pith_number":"pith:2XONVLZN","canonical_record":{"source":{"id":"2205.09442","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-19T09:57:45Z","cross_cats_sorted":[],"title_canon_sha256":"f4811da023963ddaa07a6e830199266684fddfff516b50c9f248208adc1eba17","abstract_canon_sha256":"76b2e7e8bfb2032151bf1c5d33f6d0caa14f8634b37d493ba274f75d3877b998"},"schema_version":"1.0"},"canonical_sha256":"d5dcdaaf2d103387808917e1456d9d05d8bc5a8a7fda502a83f9279451a5ba3d","source":{"kind":"arxiv","id":"2205.09442","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09442","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09442v2","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09442","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_12","alias_value":"2XONVLZNCAZY","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_16","alias_value":"2XONVLZNCAZYPAEJ","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_8","alias_value":"2XONVLZN","created_at":"2026-07-05T07:44:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:2XONVLZNCAZYPAEJC7QUK3M5AX","target":"record","payload":{"canonical_record":{"source":{"id":"2205.09442","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-19T09:57:45Z","cross_cats_sorted":[],"title_canon_sha256":"f4811da023963ddaa07a6e830199266684fddfff516b50c9f248208adc1eba17","abstract_canon_sha256":"76b2e7e8bfb2032151bf1c5d33f6d0caa14f8634b37d493ba274f75d3877b998"},"schema_version":"1.0"},"canonical_sha256":"d5dcdaaf2d103387808917e1456d9d05d8bc5a8a7fda502a83f9279451a5ba3d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:44:40.163723Z","signature_b64":"gU5jw1jWRR+iZX2iA7zMSOvsfiM0xgHBknbOcoSrNtEGkEWWzk5wetHlYO9IBOo93BQoAIiXk6pqEbclIfGuAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5dcdaaf2d103387808917e1456d9d05d8bc5a8a7fda502a83f9279451a5ba3d","last_reissued_at":"2026-07-05T07:44:40.163245Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:44:40.163245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.09442","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:44:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R8a9czMjX+71fRfZnxv1UtXJab1LSvz8usK4ayW9k9aOcg+AfTgsMQh/Yg1Kk/RrytNhfkIUbrM8agGPKzJvAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T10:07:21.777258Z"},"content_sha256":"5b3b61cf2fe9e287c8b946df5433634f311e466302a23aebb29a24fc325c5ce1","schema_version":"1.0","event_id":"sha256:5b3b61cf2fe9e287c8b946df5433634f311e466302a23aebb29a24fc325c5ce1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:2XONVLZNCAZYPAEJC7QUK3M5AX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Oracle-MNIST: a Dataset of Oracle Characters for Benchmarking Machine Learning Algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mei Wang, Weihong Deng","submitted_at":"2022-05-19T09:57:45Z","abstract_excerpt":"We introduce the Oracle-MNIST dataset, comprising of 28$\\times $28 grayscale images of 30,222 ancient characters from 10 categories, for benchmarking pattern classification, with particular challenges on image noise and distortion. The training set totally consists of 27,222 images, and the test set contains 300 images per class. Oracle-MNIST shares the same data format with the original MNIST dataset, allowing for direct compatibility with all existing classifiers and systems, but it constitutes a more challenging classification task than MNIST. The images of ancient characters suffer from 1)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09442","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.09442/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:44:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z20bHhL1PWw9xoZnmJsdV14hnLUEiXiEOe3ZIk3LQA7w12o8uwFTjUEDAF7tOGKGBnYJbwE2UAV21YrnAkraDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T10:07:21.777755Z"},"content_sha256":"a57f32fc084d69ec58fb9dcbf708b84280924ca1599c4f308e2b40d3ff63f53d","schema_version":"1.0","event_id":"sha256:a57f32fc084d69ec58fb9dcbf708b84280924ca1599c4f308e2b40d3ff63f53d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/bundle.json","state_url":"https://pith.science/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T10:07:21Z","links":{"resolver":"https://pith.science/pith/2XONVLZNCAZYPAEJC7QUK3M5AX","bundle":"https://pith.science/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/bundle.json","state":"https://pith.science/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2XONVLZNCAZYPAEJC7QUK3M5AX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:2XONVLZNCAZYPAEJC7QUK3M5AX","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":"76b2e7e8bfb2032151bf1c5d33f6d0caa14f8634b37d493ba274f75d3877b998","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-19T09:57:45Z","title_canon_sha256":"f4811da023963ddaa07a6e830199266684fddfff516b50c9f248208adc1eba17"},"schema_version":"1.0","source":{"id":"2205.09442","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09442","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09442v2","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09442","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_12","alias_value":"2XONVLZNCAZY","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_16","alias_value":"2XONVLZNCAZYPAEJ","created_at":"2026-07-05T07:44:40Z"},{"alias_kind":"pith_short_8","alias_value":"2XONVLZN","created_at":"2026-07-05T07:44:40Z"}],"graph_snapshots":[{"event_id":"sha256:a57f32fc084d69ec58fb9dcbf708b84280924ca1599c4f308e2b40d3ff63f53d","target":"graph","created_at":"2026-07-05T07:44:40Z","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/2205.09442/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce the Oracle-MNIST dataset, comprising of 28$\\times $28 grayscale images of 30,222 ancient characters from 10 categories, for benchmarking pattern classification, with particular challenges on image noise and distortion. The training set totally consists of 27,222 images, and the test set contains 300 images per class. Oracle-MNIST shares the same data format with the original MNIST dataset, allowing for direct compatibility with all existing classifiers and systems, but it constitutes a more challenging classification task than MNIST. The images of ancient characters suffer from 1)","authors_text":"Mei Wang, Weihong Deng","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-19T09:57:45Z","title":"Oracle-MNIST: a Dataset of Oracle Characters for Benchmarking Machine Learning Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09442","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":"sha256:5b3b61cf2fe9e287c8b946df5433634f311e466302a23aebb29a24fc325c5ce1","target":"record","created_at":"2026-07-05T07:44:40Z","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":"76b2e7e8bfb2032151bf1c5d33f6d0caa14f8634b37d493ba274f75d3877b998","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-05-19T09:57:45Z","title_canon_sha256":"f4811da023963ddaa07a6e830199266684fddfff516b50c9f248208adc1eba17"},"schema_version":"1.0","source":{"id":"2205.09442","kind":"arxiv","version":2}},"canonical_sha256":"d5dcdaaf2d103387808917e1456d9d05d8bc5a8a7fda502a83f9279451a5ba3d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5dcdaaf2d103387808917e1456d9d05d8bc5a8a7fda502a83f9279451a5ba3d","first_computed_at":"2026-07-05T07:44:40.163245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:40.163245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gU5jw1jWRR+iZX2iA7zMSOvsfiM0xgHBknbOcoSrNtEGkEWWzk5wetHlYO9IBOo93BQoAIiXk6pqEbclIfGuAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:40.163723Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.09442","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b3b61cf2fe9e287c8b946df5433634f311e466302a23aebb29a24fc325c5ce1","sha256:a57f32fc084d69ec58fb9dcbf708b84280924ca1599c4f308e2b40d3ff63f53d"],"state_sha256":"224c2f244e8ae4eb5742e7800fda96c000faacff2e6b684b19d0927985e245e7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nqx6hZSITgboczfUDeJ/GRDnSyK+z/DWwS5HIWYHJveJWoRLQzHnihhJs/RKImS1A34FwuywIC41XqaE/cZiDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T10:07:21.781578Z","bundle_sha256":"ded28cfc9063215b5089146793190f7cb661d7c14aca529e68d6e835a24e91d8"}}