{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:CM2DMDGBEC6IQ7CPDXOHS6FU4B","short_pith_number":"pith:CM2DMDGB","schema_version":"1.0","canonical_sha256":"1334360cc120bc887c4f1ddc7978b4e05d3e6da356fbfddcba6987f74f9582a6","source":{"kind":"arxiv","id":"2410.07804","version":3},"attestation_state":"computed","paper":{"title":"Intuitive interaction flow: A Dual-Loop Human-Machine Collaboration Task Allocation Model and an experimental study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Jiang Xu, Jingru Pei, Lingyun Sun, Qichao Zhao, Qiyang Miao, Tianyang Yu, Yilin Lu, Ziyuan Huang","submitted_at":"2024-10-10T10:45:08Z","abstract_excerpt":"This study investigates the issue of task allocation in Human-Machine Collaboration (HMC) within the context of Industry 4.0. By integrating philosophical insights and cognitive science, it clearly defines two typical modes of human behavior in human-machine interaction(HMI): skill-based intuitive behavior and knowledge-based intellectual behavior. Building on this, the concept of 'intuitive interaction flow' is innovatively introduced by combining human intuition with machine humanoid intelligence, leading to the construction of a dual-loop HMC task allocation model. Through comparative exper"},"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":"2410.07804","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-10-10T10:45:08Z","cross_cats_sorted":[],"title_canon_sha256":"86d91cc934a1670fa60ec60b24b92f1c7aaba9d1f09d3b7f5e3e83ae4b81c4ee","abstract_canon_sha256":"1abcbb361b0b11ebc49dd11529f7d9b53cf7c2297eefdebd9f0f6248c97b3d6b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:21:49.597842Z","signature_b64":"QLXjJEyhGLlrgjxQLKZUn03+xSOn+VMR3jexjaSbaTmEN8iOUpfunH73DvyrjBJ4iPCXUNKiZffBOkPD3h3wDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1334360cc120bc887c4f1ddc7978b4e05d3e6da356fbfddcba6987f74f9582a6","last_reissued_at":"2026-07-05T09:21:49.597397Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:21:49.597397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Intuitive interaction flow: A Dual-Loop Human-Machine Collaboration Task Allocation Model and an experimental study","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Jiang Xu, Jingru Pei, Lingyun Sun, Qichao Zhao, Qiyang Miao, Tianyang Yu, Yilin Lu, Ziyuan Huang","submitted_at":"2024-10-10T10:45:08Z","abstract_excerpt":"This study investigates the issue of task allocation in Human-Machine Collaboration (HMC) within the context of Industry 4.0. By integrating philosophical insights and cognitive science, it clearly defines two typical modes of human behavior in human-machine interaction(HMI): skill-based intuitive behavior and knowledge-based intellectual behavior. Building on this, the concept of 'intuitive interaction flow' is innovatively introduced by combining human intuition with machine humanoid intelligence, leading to the construction of a dual-loop HMC task allocation model. Through comparative exper"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.07804","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/2410.07804/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":"2410.07804","created_at":"2026-07-05T09:21:49.597460+00:00"},{"alias_kind":"arxiv_version","alias_value":"2410.07804v3","created_at":"2026-07-05T09:21:49.597460+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.07804","created_at":"2026-07-05T09:21:49.597460+00:00"},{"alias_kind":"pith_short_12","alias_value":"CM2DMDGBEC6I","created_at":"2026-07-05T09:21:49.597460+00:00"},{"alias_kind":"pith_short_16","alias_value":"CM2DMDGBEC6IQ7CP","created_at":"2026-07-05T09:21:49.597460+00:00"},{"alias_kind":"pith_short_8","alias_value":"CM2DMDGB","created_at":"2026-07-05T09:21:49.597460+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/CM2DMDGBEC6IQ7CPDXOHS6FU4B","json":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B.json","graph_json":"https://pith.science/api/pith-number/CM2DMDGBEC6IQ7CPDXOHS6FU4B/graph.json","events_json":"https://pith.science/api/pith-number/CM2DMDGBEC6IQ7CPDXOHS6FU4B/events.json","paper":"https://pith.science/paper/CM2DMDGB"},"agent_actions":{"view_html":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B","download_json":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B.json","view_paper":"https://pith.science/paper/CM2DMDGB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2410.07804&json=true","fetch_graph":"https://pith.science/api/pith-number/CM2DMDGBEC6IQ7CPDXOHS6FU4B/graph.json","fetch_events":"https://pith.science/api/pith-number/CM2DMDGBEC6IQ7CPDXOHS6FU4B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B/action/storage_attestation","attest_author":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B/action/author_attestation","sign_citation":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B/action/citation_signature","submit_replication":"https://pith.science/pith/CM2DMDGBEC6IQ7CPDXOHS6FU4B/action/replication_record"}},"created_at":"2026-07-05T09:21:49.597460+00:00","updated_at":"2026-07-05T09:21:49.597460+00:00"}