{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:QE4AX6PCDIQ5XO27GGLY33NC4F","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":"6c4e6b55caada6248dc17f5d06b37672a5a5aaf6ff2b7ce50c6dce32bea54eaf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2019-08-08T17:20:24Z","title_canon_sha256":"904b840066efcee0e1bb50ccabacd4dfc5b0b05f4e86d3dbdf6eada477a856f7"},"schema_version":"1.0","source":{"id":"1908.03180","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.03180","created_at":"2026-07-04T23:52:26Z"},{"alias_kind":"arxiv_version","alias_value":"1908.03180v1","created_at":"2026-07-04T23:52:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.03180","created_at":"2026-07-04T23:52:26Z"},{"alias_kind":"pith_short_12","alias_value":"QE4AX6PCDIQ5","created_at":"2026-07-04T23:52:26Z"},{"alias_kind":"pith_short_16","alias_value":"QE4AX6PCDIQ5XO27","created_at":"2026-07-04T23:52:26Z"},{"alias_kind":"pith_short_8","alias_value":"QE4AX6PC","created_at":"2026-07-04T23:52:26Z"}],"graph_snapshots":[{"event_id":"sha256:6e300524e7e0f520f871271a2c66e39d1007cfe408aedd85d72c5d7acdfb9bf0","target":"graph","created_at":"2026-07-04T23:52:26Z","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/1908.03180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Film media is a rich form of artistic expression. Unlike photography, and short videos, movies contain a storyline that is deliberately complex and intricate in order to engage its audience. In this paper we present a large scale study comparing the effectiveness of visual, audio, text, and metadata-based features for predicting high-level information about movies such as their genre or estimated budget. We demonstrate the usefulness of content-based methods in this domain in contrast to human-based and metadata-based predictions in the era of deep learning. Additionally, we provide a comprehe","authors_text":"Kalpathy Sitaraman, Mengjia Luo, Paola Cascante-Bonilla, Vicente Ordonez","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2019-08-08T17:20:24Z","title":"Moviescope: Large-scale Analysis of Movies using Multiple Modalities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.03180","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:d50ea7283f19f61a048b510a1e0a48937632d40ff1d855848fc00358512673c8","target":"record","created_at":"2026-07-04T23:52:26Z","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":"6c4e6b55caada6248dc17f5d06b37672a5a5aaf6ff2b7ce50c6dce32bea54eaf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2019-08-08T17:20:24Z","title_canon_sha256":"904b840066efcee0e1bb50ccabacd4dfc5b0b05f4e86d3dbdf6eada477a856f7"},"schema_version":"1.0","source":{"id":"1908.03180","kind":"arxiv","version":1}},"canonical_sha256":"81380bf9e21a21dbbb5f31978deda2e16ef71357d38074468b5b05b66f04c093","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81380bf9e21a21dbbb5f31978deda2e16ef71357d38074468b5b05b66f04c093","first_computed_at":"2026-07-04T23:52:26.945480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:52:26.945480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JBwqtyCKA5fk+MJ8Dk+Khc2IavPEeuXUKwtjO+rC+L1T3VENLML8hUMI6j+bEvvMK+mEhtewi8yyoLSmbzRiAQ==","signature_status":"signed_v1","signed_at":"2026-07-04T23:52:26.945838Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.03180","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d50ea7283f19f61a048b510a1e0a48937632d40ff1d855848fc00358512673c8","sha256:6e300524e7e0f520f871271a2c66e39d1007cfe408aedd85d72c5d7acdfb9bf0"],"state_sha256":"dd414b4c7d8d5a9eeccd204e6243b4cda4876c7d73dc2d290174316fc2386f92"}