{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:Y6AGNVQMLPCBV2MXHI6TBGI6I4","short_pith_number":"pith:Y6AGNVQM","canonical_record":{"source":{"id":"2301.08140","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-19T15:54:52Z","cross_cats_sorted":[],"title_canon_sha256":"1e2761fdc35b5a52ca70c96cf4978f3e091a4ee82ad149fac7abe1b5c6a8b3b4","abstract_canon_sha256":"de8482dd20b6238805555579fd8e82ae2a0cced1c13016e4fcd3b27084f691b9"},"schema_version":"1.0"},"canonical_sha256":"c78066d60c5bc41ae9973a3d30991e4717b8602636cac3c849186e00c2402db9","source":{"kind":"arxiv","id":"2301.08140","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08140","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08140v1","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08140","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_12","alias_value":"Y6AGNVQMLPCB","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_16","alias_value":"Y6AGNVQMLPCBV2MX","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_8","alias_value":"Y6AGNVQM","created_at":"2026-07-05T05:58:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:Y6AGNVQMLPCBV2MXHI6TBGI6I4","target":"record","payload":{"canonical_record":{"source":{"id":"2301.08140","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-19T15:54:52Z","cross_cats_sorted":[],"title_canon_sha256":"1e2761fdc35b5a52ca70c96cf4978f3e091a4ee82ad149fac7abe1b5c6a8b3b4","abstract_canon_sha256":"de8482dd20b6238805555579fd8e82ae2a0cced1c13016e4fcd3b27084f691b9"},"schema_version":"1.0"},"canonical_sha256":"c78066d60c5bc41ae9973a3d30991e4717b8602636cac3c849186e00c2402db9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:58:19.279142Z","signature_b64":"EtLqUHFhha7LBECRTU1wsXR1iH2AG7jzvQEgwpChzPqy+4fdAUqTMsWr4LVrsbRCN6dxAuU6TlmjDRm9FmXHAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c78066d60c5bc41ae9973a3d30991e4717b8602636cac3c849186e00c2402db9","last_reissued_at":"2026-07-05T05:58:19.278715Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:58:19.278715Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.08140","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:58:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zLYiMeB9M/KRH/EmtJFyPbocvi+qsYuE127ZiQKN3BkRvBuJO9/9V1fKnaFBYOX4xi//uoIkkTLjZXeYOHAKAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:52:19.993388Z"},"content_sha256":"f9f292cf405ada7a1eeb4ac7df0687e6314d1de53680c612d7e4312a9c3454e8","schema_version":"1.0","event_id":"sha256:f9f292cf405ada7a1eeb4ac7df0687e6314d1de53680c612d7e4312a9c3454e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:Y6AGNVQMLPCBV2MXHI6TBGI6I4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Regularising disparity estimation via multi task learning with structured light reconstruction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alistair Weld, Chi Xu, Joao Cartucho, Joseph Davids, Stamatia Giannarou","submitted_at":"2023-01-19T15:54:52Z","abstract_excerpt":"3D reconstruction is a useful tool for surgical planning and guidance. However, the lack of available medical data stunts research and development in this field, as supervised deep learning methods for accurate disparity estimation rely heavily on large datasets containing ground truth information. Alternative approaches to supervision have been explored, such as self-supervision, which can reduce or remove entirely the need for ground truth. However, no proposed alternatives have demonstrated performance capabilities close to what would be expected from a supervised setup. This work aims to a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08140","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/2301.08140/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":"2026-07-05T05:58:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bYVMxV101npc6/YZxdYYtVTSe027YgsVqrKjT1TH4rJCZJktuH1cnavEI5n3lQmybuk0JeBM9utfx4Yn2zgICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:52:19.993896Z"},"content_sha256":"f8d10e051cffbd10abc02d6fb3060f3cab17d3581e1079d41ed4cc84f7035864","schema_version":"1.0","event_id":"sha256:f8d10e051cffbd10abc02d6fb3060f3cab17d3581e1079d41ed4cc84f7035864"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/bundle.json","state_url":"https://pith.science/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/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":"2026-08-14T06:52:19Z","links":{"resolver":"https://pith.science/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4","bundle":"https://pith.science/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/bundle.json","state":"https://pith.science/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y6AGNVQMLPCBV2MXHI6TBGI6I4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:Y6AGNVQMLPCBV2MXHI6TBGI6I4","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":"de8482dd20b6238805555579fd8e82ae2a0cced1c13016e4fcd3b27084f691b9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-19T15:54:52Z","title_canon_sha256":"1e2761fdc35b5a52ca70c96cf4978f3e091a4ee82ad149fac7abe1b5c6a8b3b4"},"schema_version":"1.0","source":{"id":"2301.08140","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08140","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08140v1","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08140","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_12","alias_value":"Y6AGNVQMLPCB","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_16","alias_value":"Y6AGNVQMLPCBV2MX","created_at":"2026-07-05T05:58:19Z"},{"alias_kind":"pith_short_8","alias_value":"Y6AGNVQM","created_at":"2026-07-05T05:58:19Z"}],"graph_snapshots":[{"event_id":"sha256:f8d10e051cffbd10abc02d6fb3060f3cab17d3581e1079d41ed4cc84f7035864","target":"graph","created_at":"2026-07-05T05:58:19Z","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/2301.08140/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D reconstruction is a useful tool for surgical planning and guidance. However, the lack of available medical data stunts research and development in this field, as supervised deep learning methods for accurate disparity estimation rely heavily on large datasets containing ground truth information. Alternative approaches to supervision have been explored, such as self-supervision, which can reduce or remove entirely the need for ground truth. However, no proposed alternatives have demonstrated performance capabilities close to what would be expected from a supervised setup. This work aims to a","authors_text":"Alistair Weld, Chi Xu, Joao Cartucho, Joseph Davids, Stamatia Giannarou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-19T15:54:52Z","title":"Regularising disparity estimation via multi task learning with structured light reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08140","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:f9f292cf405ada7a1eeb4ac7df0687e6314d1de53680c612d7e4312a9c3454e8","target":"record","created_at":"2026-07-05T05:58:19Z","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":"de8482dd20b6238805555579fd8e82ae2a0cced1c13016e4fcd3b27084f691b9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-01-19T15:54:52Z","title_canon_sha256":"1e2761fdc35b5a52ca70c96cf4978f3e091a4ee82ad149fac7abe1b5c6a8b3b4"},"schema_version":"1.0","source":{"id":"2301.08140","kind":"arxiv","version":1}},"canonical_sha256":"c78066d60c5bc41ae9973a3d30991e4717b8602636cac3c849186e00c2402db9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c78066d60c5bc41ae9973a3d30991e4717b8602636cac3c849186e00c2402db9","first_computed_at":"2026-07-05T05:58:19.278715Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:58:19.278715Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EtLqUHFhha7LBECRTU1wsXR1iH2AG7jzvQEgwpChzPqy+4fdAUqTMsWr4LVrsbRCN6dxAuU6TlmjDRm9FmXHAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:58:19.279142Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.08140","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9f292cf405ada7a1eeb4ac7df0687e6314d1de53680c612d7e4312a9c3454e8","sha256:f8d10e051cffbd10abc02d6fb3060f3cab17d3581e1079d41ed4cc84f7035864"],"state_sha256":"be90fdf855a0011d5eb804c12abdeb66593667c45fcaf88a0db20208fcf444e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YLM8v5e0YTqyZSKSJQGvtf0YJ28xrdmzqnnhoVliDEHSjYpm03CUkBLTpoSbHyCyTnahG2bljwm9YTKSRjRiDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T06:52:19.998575Z","bundle_sha256":"72b938e523a4c790a6bc792f45499ab300bde37b642dfb84fa17b71c223082ab"}}