{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:MJ7GUBLH3X2BDJB5POMJHGNVCU","short_pith_number":"pith:MJ7GUBLH","canonical_record":{"source":{"id":"1805.07339","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T17:43:55Z","cross_cats_sorted":["cs.DC","cs.GR"],"title_canon_sha256":"09340cce1891e8ec614bb8e2bac03b570c07e83d0b8c14d36be40f473acbfcf6","abstract_canon_sha256":"d9a893d456325ae3e277babe483ea4d9b2e4dffaeac6cb445146a5e597f94797"},"schema_version":"1.0"},"canonical_sha256":"627e6a0567ddf411a43d7b989399b5153e5d4e9739ae822e48a89660c9199c45","source":{"kind":"arxiv","id":"1805.07339","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.07339","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"arxiv_version","alias_value":"1805.07339v1","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.07339","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"pith_short_12","alias_value":"MJ7GUBLH3X2B","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"MJ7GUBLH3X2BDJB5","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"MJ7GUBLH","created_at":"2026-05-18T12:32:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:MJ7GUBLH3X2BDJB5POMJHGNVCU","target":"record","payload":{"canonical_record":{"source":{"id":"1805.07339","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T17:43:55Z","cross_cats_sorted":["cs.DC","cs.GR"],"title_canon_sha256":"09340cce1891e8ec614bb8e2bac03b570c07e83d0b8c14d36be40f473acbfcf6","abstract_canon_sha256":"d9a893d456325ae3e277babe483ea4d9b2e4dffaeac6cb445146a5e597f94797"},"schema_version":"1.0"},"canonical_sha256":"627e6a0567ddf411a43d7b989399b5153e5d4e9739ae822e48a89660c9199c45","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:38.494786Z","signature_b64":"5ADl2OBNLlz8AjKkeUvvceVOpCphkVIcetPn+z5OtBrK2EHrqZRNlGrCsEgDy9EM+Kk8vw1R0+4lJ7asB0fADA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"627e6a0567ddf411a43d7b989399b5153e5d4e9739ae822e48a89660c9199c45","last_reissued_at":"2026-05-18T00:15:38.494236Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:38.494236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.07339","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:15:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QBXyC02bMzuwxjWG1aXzzsEPpucnjEHqf7fsGy1Yrrw7f5xgrEtpkiQ5CZ5GPuA7fqAtkBVJiJxxbDOqUxh8DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T11:10:45.809719Z"},"content_sha256":"0449fdf1341697ffa8fe6ee365b4fc365a19482b7f1b441fbaeddc4080d371c9","schema_version":"1.0","event_id":"sha256:0449fdf1341697ffa8fe6ee365b4fc365a19482b7f1b441fbaeddc4080d371c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:MJ7GUBLH3X2BDJB5POMJHGNVCU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scanner: Efficient Video Analysis at Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC","cs.GR"],"primary_cat":"cs.CV","authors_text":"Alex Poms, Kayvon Fatahalian, Pat Hanrahan, Will Crichton","submitted_at":"2018-05-18T17:43:55Z","abstract_excerpt":"A growing number of visual computing applications depend on the analysis of large video collections. The challenge is that scaling applications to operate on these datasets requires efficient systems for pixel data access and parallel processing across large numbers of machines. Few programmers have the capability to operate efficiently at these scales, limiting the field's ability to explore new applications that leverage big video data. In response, we have created Scanner, a system for productive and efficient video analysis at scale. Scanner organizes video collections as tables in a data "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.07339","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":""},"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":"2026-05-18T00:15:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"itrtd92psc0tj5z+YdSMljGp033nMQ0BFaYEbnqfslZyD2nXX3Cy/df8AFAouktuNnqL4bTCwo1A6Mt2PeHECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T11:10:45.810061Z"},"content_sha256":"9c5f1c52acf1798e2500e7cbbeca479152f962fb2a5e3cb1bbb3415b57670b9c","schema_version":"1.0","event_id":"sha256:9c5f1c52acf1798e2500e7cbbeca479152f962fb2a5e3cb1bbb3415b57670b9c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/bundle.json","state_url":"https://pith.science/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/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":"2026-06-09T11:10:45Z","links":{"resolver":"https://pith.science/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU","bundle":"https://pith.science/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/bundle.json","state":"https://pith.science/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MJ7GUBLH3X2BDJB5POMJHGNVCU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:MJ7GUBLH3X2BDJB5POMJHGNVCU","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":"d9a893d456325ae3e277babe483ea4d9b2e4dffaeac6cb445146a5e597f94797","cross_cats_sorted":["cs.DC","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T17:43:55Z","title_canon_sha256":"09340cce1891e8ec614bb8e2bac03b570c07e83d0b8c14d36be40f473acbfcf6"},"schema_version":"1.0","source":{"id":"1805.07339","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.07339","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"arxiv_version","alias_value":"1805.07339v1","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.07339","created_at":"2026-05-18T00:15:38Z"},{"alias_kind":"pith_short_12","alias_value":"MJ7GUBLH3X2B","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"MJ7GUBLH3X2BDJB5","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"MJ7GUBLH","created_at":"2026-05-18T12:32:37Z"}],"graph_snapshots":[{"event_id":"sha256:9c5f1c52acf1798e2500e7cbbeca479152f962fb2a5e3cb1bbb3415b57670b9c","target":"graph","created_at":"2026-05-18T00:15:38Z","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"},"paper":{"abstract_excerpt":"A growing number of visual computing applications depend on the analysis of large video collections. The challenge is that scaling applications to operate on these datasets requires efficient systems for pixel data access and parallel processing across large numbers of machines. Few programmers have the capability to operate efficiently at these scales, limiting the field's ability to explore new applications that leverage big video data. In response, we have created Scanner, a system for productive and efficient video analysis at scale. Scanner organizes video collections as tables in a data ","authors_text":"Alex Poms, Kayvon Fatahalian, Pat Hanrahan, Will Crichton","cross_cats":["cs.DC","cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T17:43:55Z","title":"Scanner: Efficient Video Analysis at Scale"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.07339","kind":"arxiv","version":1},"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":"sha256:0449fdf1341697ffa8fe6ee365b4fc365a19482b7f1b441fbaeddc4080d371c9","target":"record","created_at":"2026-05-18T00:15:38Z","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":"d9a893d456325ae3e277babe483ea4d9b2e4dffaeac6cb445146a5e597f94797","cross_cats_sorted":["cs.DC","cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-18T17:43:55Z","title_canon_sha256":"09340cce1891e8ec614bb8e2bac03b570c07e83d0b8c14d36be40f473acbfcf6"},"schema_version":"1.0","source":{"id":"1805.07339","kind":"arxiv","version":1}},"canonical_sha256":"627e6a0567ddf411a43d7b989399b5153e5d4e9739ae822e48a89660c9199c45","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"627e6a0567ddf411a43d7b989399b5153e5d4e9739ae822e48a89660c9199c45","first_computed_at":"2026-05-18T00:15:38.494236Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:38.494236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5ADl2OBNLlz8AjKkeUvvceVOpCphkVIcetPn+z5OtBrK2EHrqZRNlGrCsEgDy9EM+Kk8vw1R0+4lJ7asB0fADA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:38.494786Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.07339","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0449fdf1341697ffa8fe6ee365b4fc365a19482b7f1b441fbaeddc4080d371c9","sha256:9c5f1c52acf1798e2500e7cbbeca479152f962fb2a5e3cb1bbb3415b57670b9c"],"state_sha256":"6ab08d65583fa97f86a939984a4e22837e24280d453b772f50099ee1d66fcae2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7ZmRcbt2+8gY7rlMqHD66qetS2z27gk6BouxaHdAd+ETBd4ykws7LJ8HELcdK9YRjIZpx2MKiwxe+JSt72C9Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T11:10:45.811860Z","bundle_sha256":"78aa1ce10e525dc2f1782a993b5ac405a9a92814eca0f01fefb9987f9e1cd4d3"}}