{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:SZADTLYZ43ZB5K7NFHAIKHKZ2I","short_pith_number":"pith:SZADTLYZ","schema_version":"1.0","canonical_sha256":"964039af19e6f21eabed29c0851d59d237f231ee8dca9e6886c4c93f72268e75","source":{"kind":"arxiv","id":"2303.13527","version":1},"attestation_state":"computed","paper":{"title":"Dataset for predicting cybersickness from a virtual navigation task","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Jean-R\\'emy Chardonnet, Pan Hui, Ruichen Li, Yuyang Wang","submitted_at":"2023-02-07T03:57:56Z","abstract_excerpt":"This work presents a dataset collected to predict cybersickness in virtual reality environments. The data was collected from navigation tasks in a virtual environment designed to induce cybersickness. The dataset consists of many data points collected from diverse participants, including physiological responses (EDA and Heart Rate) and self-reported cybersickness symptoms. The paper will provide a detailed description of the dataset, including the arranged navigation task, the data collection procedures, and the data format. The dataset will serve as a valuable resource for researchers to deve"},"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":"2303.13527","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2023-02-07T03:57:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"56afb5002386ba9555bca749862376474e37aa7c1067eb25680f373e395f3975","abstract_canon_sha256":"46f91eb7a8356ce6d18c1f9ba684e131abede30d07dde7a9e47e080f837088d5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:54:04.140906Z","signature_b64":"H1V01dsgOLCJ0c+bgHIJssV+TGLSY+UI14pPxQZwj9/a5+zxZMoiGpDBb0A3+Yz661AFpm0buEW413tfCT9xCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"964039af19e6f21eabed29c0851d59d237f231ee8dca9e6886c4c93f72268e75","last_reissued_at":"2026-07-05T05:54:04.140446Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:54:04.140446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dataset for predicting cybersickness from a virtual navigation task","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Jean-R\\'emy Chardonnet, Pan Hui, Ruichen Li, Yuyang Wang","submitted_at":"2023-02-07T03:57:56Z","abstract_excerpt":"This work presents a dataset collected to predict cybersickness in virtual reality environments. The data was collected from navigation tasks in a virtual environment designed to induce cybersickness. The dataset consists of many data points collected from diverse participants, including physiological responses (EDA and Heart Rate) and self-reported cybersickness symptoms. The paper will provide a detailed description of the dataset, including the arranged navigation task, the data collection procedures, and the data format. The dataset will serve as a valuable resource for researchers to deve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.13527","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2303.13527/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":"2303.13527","created_at":"2026-07-05T05:54:04.140506+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.13527v1","created_at":"2026-07-05T05:54:04.140506+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.13527","created_at":"2026-07-05T05:54:04.140506+00:00"},{"alias_kind":"pith_short_12","alias_value":"SZADTLYZ43ZB","created_at":"2026-07-05T05:54:04.140506+00:00"},{"alias_kind":"pith_short_16","alias_value":"SZADTLYZ43ZB5K7N","created_at":"2026-07-05T05:54:04.140506+00:00"},{"alias_kind":"pith_short_8","alias_value":"SZADTLYZ","created_at":"2026-07-05T05:54:04.140506+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.06698","citing_title":"A comparative study of sensory encoding models for human navigation in virtual reality","ref_index":29,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I","json":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I.json","graph_json":"https://pith.science/api/pith-number/SZADTLYZ43ZB5K7NFHAIKHKZ2I/graph.json","events_json":"https://pith.science/api/pith-number/SZADTLYZ43ZB5K7NFHAIKHKZ2I/events.json","paper":"https://pith.science/paper/SZADTLYZ"},"agent_actions":{"view_html":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I","download_json":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I.json","view_paper":"https://pith.science/paper/SZADTLYZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.13527&json=true","fetch_graph":"https://pith.science/api/pith-number/SZADTLYZ43ZB5K7NFHAIKHKZ2I/graph.json","fetch_events":"https://pith.science/api/pith-number/SZADTLYZ43ZB5K7NFHAIKHKZ2I/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I/action/storage_attestation","attest_author":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I/action/author_attestation","sign_citation":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I/action/citation_signature","submit_replication":"https://pith.science/pith/SZADTLYZ43ZB5K7NFHAIKHKZ2I/action/replication_record"}},"created_at":"2026-07-05T05:54:04.140506+00:00","updated_at":"2026-07-05T05:54:04.140506+00:00"}