{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FYNLVTUV3OT4RXZMTTKIPR6QLS","short_pith_number":"pith:FYNLVTUV","canonical_record":{"source":{"id":"2411.05985","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-08T21:42:50Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"6d06025e02869f17407d201b82b56e4fbc993d8ab8d4f8d5f03ff099c33a5849","abstract_canon_sha256":"59f3a181b4bce544aa5cc1fc11c68585722cc66f118ddd00e0a390ed2a70fcd7"},"schema_version":"1.0"},"canonical_sha256":"2e1abace95dba7c8df2c9cd487c7d05c98408d8f1d2bb8de989dc3127bb37d62","source":{"kind":"arxiv","id":"2411.05985","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.05985","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"arxiv_version","alias_value":"2411.05985v3","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.05985","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_12","alias_value":"FYNLVTUV3OT4","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_16","alias_value":"FYNLVTUV3OT4RXZM","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_8","alias_value":"FYNLVTUV","created_at":"2026-06-23T01:11:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FYNLVTUV3OT4RXZMTTKIPR6QLS","target":"record","payload":{"canonical_record":{"source":{"id":"2411.05985","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-08T21:42:50Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"6d06025e02869f17407d201b82b56e4fbc993d8ab8d4f8d5f03ff099c33a5849","abstract_canon_sha256":"59f3a181b4bce544aa5cc1fc11c68585722cc66f118ddd00e0a390ed2a70fcd7"},"schema_version":"1.0"},"canonical_sha256":"2e1abace95dba7c8df2c9cd487c7d05c98408d8f1d2bb8de989dc3127bb37d62","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T01:11:53.377613Z","signature_b64":"cr8KDHg5r/fHucIt+GUHmnqJpd7iK6NpN5UfeZy6FyrpOx+JzTUQQX98wrrrmfEe7vm0AV07ef7kRVHSOg12Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e1abace95dba7c8df2c9cd487c7d05c98408d8f1d2bb8de989dc3127bb37d62","last_reissued_at":"2026-06-23T01:11:53.377086Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T01:11:53.377086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.05985","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-23T01:11:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6No3cRkWwBgTBRIN6a/7HddazDEzP2PEr3Nt3RXb+hjJaS6mfeeRYztwZML82+tRdEyWl5rtnCFArC/tAPtPBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:12:21.577914Z"},"content_sha256":"870bc2c5385dfe24d02a248acd6a7bea29ebabacbe6483ba311a98b00226fed9","schema_version":"1.0","event_id":"sha256:870bc2c5385dfe24d02a248acd6a7bea29ebabacbe6483ba311a98b00226fed9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FYNLVTUV3OT4RXZMTTKIPR6QLS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Fearful Images: Investigating Potential Emotional Biases in Image-Generation Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CY","authors_text":"Cody Buntain, Maneet Mehta","submitted_at":"2024-11-08T21:42:50Z","abstract_excerpt":"This paper examines potential biases and inconsistencies in the emotions evoked by images produced by generative artificial intelligence (AI) models and their potential bias toward negative emotions. We assess this bias by comparing the emotions evoked by an AI-produced image to the emotions evoked by prompts used to create those images. After developing and validating automated methods for emotion recognition across modalities, we examine correlations in the prevalence of emotions across text and images and measure the degree to which generative AI models tend to over-represent specific emoti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.05985","kind":"arxiv","version":3},"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/2411.05985/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":"2026-06-23T01:11:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gH/tWoCj3YtNXzrL0XdH2t1dtw2UtxEx4+I+Dzs6a19KG1OaLd19WRHwk6j69GStSq/TrOYbGIgsjEsNdTxzCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:12:21.578424Z"},"content_sha256":"4095755d21631996a83d17f4b81ddc05177cc73f594b0acc51e959b18e1d20d9","schema_version":"1.0","event_id":"sha256:4095755d21631996a83d17f4b81ddc05177cc73f594b0acc51e959b18e1d20d9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/bundle.json","state_url":"https://pith.science/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/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":"2026-08-07T12:12:21Z","links":{"resolver":"https://pith.science/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS","bundle":"https://pith.science/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/bundle.json","state":"https://pith.science/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FYNLVTUV3OT4RXZMTTKIPR6QLS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FYNLVTUV3OT4RXZMTTKIPR6QLS","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":"59f3a181b4bce544aa5cc1fc11c68585722cc66f118ddd00e0a390ed2a70fcd7","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-08T21:42:50Z","title_canon_sha256":"6d06025e02869f17407d201b82b56e4fbc993d8ab8d4f8d5f03ff099c33a5849"},"schema_version":"1.0","source":{"id":"2411.05985","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.05985","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"arxiv_version","alias_value":"2411.05985v3","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.05985","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_12","alias_value":"FYNLVTUV3OT4","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_16","alias_value":"FYNLVTUV3OT4RXZM","created_at":"2026-06-23T01:11:53Z"},{"alias_kind":"pith_short_8","alias_value":"FYNLVTUV","created_at":"2026-06-23T01:11:53Z"}],"graph_snapshots":[{"event_id":"sha256:4095755d21631996a83d17f4b81ddc05177cc73f594b0acc51e959b18e1d20d9","target":"graph","created_at":"2026-06-23T01:11:53Z","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/2411.05985/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper examines potential biases and inconsistencies in the emotions evoked by images produced by generative artificial intelligence (AI) models and their potential bias toward negative emotions. We assess this bias by comparing the emotions evoked by an AI-produced image to the emotions evoked by prompts used to create those images. After developing and validating automated methods for emotion recognition across modalities, we examine correlations in the prevalence of emotions across text and images and measure the degree to which generative AI models tend to over-represent specific emoti","authors_text":"Cody Buntain, Maneet Mehta","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-08T21:42:50Z","title":"Generating Fearful Images: Investigating Potential Emotional Biases in Image-Generation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.05985","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":"sha256:870bc2c5385dfe24d02a248acd6a7bea29ebabacbe6483ba311a98b00226fed9","target":"record","created_at":"2026-06-23T01:11:53Z","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":"59f3a181b4bce544aa5cc1fc11c68585722cc66f118ddd00e0a390ed2a70fcd7","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-11-08T21:42:50Z","title_canon_sha256":"6d06025e02869f17407d201b82b56e4fbc993d8ab8d4f8d5f03ff099c33a5849"},"schema_version":"1.0","source":{"id":"2411.05985","kind":"arxiv","version":3}},"canonical_sha256":"2e1abace95dba7c8df2c9cd487c7d05c98408d8f1d2bb8de989dc3127bb37d62","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e1abace95dba7c8df2c9cd487c7d05c98408d8f1d2bb8de989dc3127bb37d62","first_computed_at":"2026-06-23T01:11:53.377086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T01:11:53.377086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cr8KDHg5r/fHucIt+GUHmnqJpd7iK6NpN5UfeZy6FyrpOx+JzTUQQX98wrrrmfEe7vm0AV07ef7kRVHSOg12Bw==","signature_status":"signed_v1","signed_at":"2026-06-23T01:11:53.377613Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.05985","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:870bc2c5385dfe24d02a248acd6a7bea29ebabacbe6483ba311a98b00226fed9","sha256:4095755d21631996a83d17f4b81ddc05177cc73f594b0acc51e959b18e1d20d9"],"state_sha256":"e17599ff922fa62044cf1a82e6034276028c0ab881e3e3ac50e30f974bbb390e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXDGD+lL+4xhKu3Eu/bB4yykSlBZnI8/jI0RFNuIlWupCilAFvMtV4hG4GZpEMhNg/ip3ypJ3vrzUSl1d4rQAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T12:12:21.582743Z","bundle_sha256":"0a8dfae344df0de33fe36e35ecf7cffcf67d4fa34fa3af48aabff0a277973faa"}}