{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:O43VHMZT2MTDMBRCCHZ7BVZMJX","short_pith_number":"pith:O43VHMZT","schema_version":"1.0","canonical_sha256":"773753b333d32636062211f3f0d72c4dc9dba65c28dd0536a2a9e215759cfc38","source":{"kind":"arxiv","id":"2204.09316","version":2},"attestation_state":"computed","paper":{"title":"Massive Twinning to Enhance Emergent Intelligence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.MA","authors_text":"Bin Han, Dennis Krummacker, Hans D. Schotten, Siyu Yuan","submitted_at":"2022-04-20T08:51:06Z","abstract_excerpt":"As a complement to conventional AI solutions, emergent intelligence (EI) exhibits competitiveness in 6G IIoT scenario for its various outstanding features including robustness, protection to privacy, and scalability. However, despite the low computational complexity, EI is challenged by its high demand of data traffic in massive deployment. We propose to leverage massive twinning, which 6G is envisaged to support, to reduce the data traffic in EI and therewith enhance its performance."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2204.09316","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2022-04-20T08:51:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bfef16d07fafb6c645f13a059704d94ad441609401b88d4529554be3776813b5","abstract_canon_sha256":"c50ad2ba4662f7c56a0a794751ca0884af1f552aafce44a1737834446902e954"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:13:06.424571Z","signature_b64":"Ji2m6S1Q8UPagDHPS29KO2sg/MtiOOGsUueZ68YWQHsXcCld93Ljm7BSfp+/Xy5Gvmrpl6q3/Jm/Uj2IJKnXBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"773753b333d32636062211f3f0d72c4dc9dba65c28dd0536a2a9e215759cfc38","last_reissued_at":"2026-07-05T05:13:06.424113Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:13:06.424113Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Massive Twinning to Enhance Emergent Intelligence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.MA","authors_text":"Bin Han, Dennis Krummacker, Hans D. Schotten, Siyu Yuan","submitted_at":"2022-04-20T08:51:06Z","abstract_excerpt":"As a complement to conventional AI solutions, emergent intelligence (EI) exhibits competitiveness in 6G IIoT scenario for its various outstanding features including robustness, protection to privacy, and scalability. However, despite the low computational complexity, EI is challenged by its high demand of data traffic in massive deployment. We propose to leverage massive twinning, which 6G is envisaged to support, to reduce the data traffic in EI and therewith enhance its performance."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.09316","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/2204.09316/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2204.09316","created_at":"2026-07-05T05:13:06.424168+00:00"},{"alias_kind":"arxiv_version","alias_value":"2204.09316v2","created_at":"2026-07-05T05:13:06.424168+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.09316","created_at":"2026-07-05T05:13:06.424168+00:00"},{"alias_kind":"pith_short_12","alias_value":"O43VHMZT2MTD","created_at":"2026-07-05T05:13:06.424168+00:00"},{"alias_kind":"pith_short_16","alias_value":"O43VHMZT2MTDMBRC","created_at":"2026-07-05T05:13:06.424168+00:00"},{"alias_kind":"pith_short_8","alias_value":"O43VHMZT","created_at":"2026-07-05T05:13:06.424168+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX","json":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX.json","graph_json":"https://pith.science/api/pith-number/O43VHMZT2MTDMBRCCHZ7BVZMJX/graph.json","events_json":"https://pith.science/api/pith-number/O43VHMZT2MTDMBRCCHZ7BVZMJX/events.json","paper":"https://pith.science/paper/O43VHMZT"},"agent_actions":{"view_html":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX","download_json":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX.json","view_paper":"https://pith.science/paper/O43VHMZT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2204.09316&json=true","fetch_graph":"https://pith.science/api/pith-number/O43VHMZT2MTDMBRCCHZ7BVZMJX/graph.json","fetch_events":"https://pith.science/api/pith-number/O43VHMZT2MTDMBRCCHZ7BVZMJX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX/action/storage_attestation","attest_author":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX/action/author_attestation","sign_citation":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX/action/citation_signature","submit_replication":"https://pith.science/pith/O43VHMZT2MTDMBRCCHZ7BVZMJX/action/replication_record"}},"created_at":"2026-07-05T05:13:06.424168+00:00","updated_at":"2026-07-05T05:13:06.424168+00:00"}