{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:IOUUATSROJZ7RI43R2C7V4DMJ5","short_pith_number":"pith:IOUUATSR","schema_version":"1.0","canonical_sha256":"43a9404e517273f8a39b8e85faf06c4f6f6a25a4437ba9932c41142a7d6fc891","source":{"kind":"arxiv","id":"2602.06989","version":2},"attestation_state":"computed","paper":{"title":"Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.geo-ph","authors_text":"Ahmed H. Elsheikh, Hannah P. Menke, Julien Maes, Kamaljit Singh, Muhammad Z. Kashim, Sebastian Geiger, Zainol A. A. Bakar, Zhenkai Bo","submitted_at":"2026-01-27T23:45:33Z","abstract_excerpt":"Carbonate reservoirs offer significant capacity for subsurface carbon storage, oil production, and underground hydrogen storage. X-ray computed tomography (X-ray CT) coupled with numerical simulations is commonly used to investigate the multiphase flow behaviors in carbonate rocks. Carbonates exhibit pore size distribution across scales, hindering the comprehensive investigation with conventional X-ray CT images. Imaging samples at both macro and micro-scales (multi-scale imaging) proved to be a viable option in this context. However, multi-scale imaging faces two key limitations: the trade-of"},"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":"2602.06989","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"physics.geo-ph","submitted_at":"2026-01-27T23:45:33Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b5115f1fb614461fe87bdd80454ce69fbd64dcdac99faee3842012004e5dabe9","abstract_canon_sha256":"befa02f18fb457c27a75afef0e36722d0de10dc1f4cbc3262fba34e0686a403a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:17:33.729664Z","signature_b64":"ZYUc3T6Di40OMFn3qze63CMk/JnvSpMBukPi4v5ujyLxPPbh0gGayyNEPwG+T10d8vHUGE/M4RvT5YPfODDkDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43a9404e517273f8a39b8e85faf06c4f6f6a25a4437ba9932c41142a7d6fc891","last_reissued_at":"2026-06-30T01:17:33.728798Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:17:33.728798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.geo-ph","authors_text":"Ahmed H. Elsheikh, Hannah P. Menke, Julien Maes, Kamaljit Singh, Muhammad Z. Kashim, Sebastian Geiger, Zainol A. A. Bakar, Zhenkai Bo","submitted_at":"2026-01-27T23:45:33Z","abstract_excerpt":"Carbonate reservoirs offer significant capacity for subsurface carbon storage, oil production, and underground hydrogen storage. X-ray computed tomography (X-ray CT) coupled with numerical simulations is commonly used to investigate the multiphase flow behaviors in carbonate rocks. Carbonates exhibit pore size distribution across scales, hindering the comprehensive investigation with conventional X-ray CT images. Imaging samples at both macro and micro-scales (multi-scale imaging) proved to be a viable option in this context. However, multi-scale imaging faces two key limitations: the trade-of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.06989","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/2602.06989/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":"2602.06989","created_at":"2026-06-30T01:17:33.728899+00:00"},{"alias_kind":"arxiv_version","alias_value":"2602.06989v2","created_at":"2026-06-30T01:17:33.728899+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.06989","created_at":"2026-06-30T01:17:33.728899+00:00"},{"alias_kind":"pith_short_12","alias_value":"IOUUATSROJZ7","created_at":"2026-06-30T01:17:33.728899+00:00"},{"alias_kind":"pith_short_16","alias_value":"IOUUATSROJZ7RI43","created_at":"2026-06-30T01:17:33.728899+00:00"},{"alias_kind":"pith_short_8","alias_value":"IOUUATSR","created_at":"2026-06-30T01:17:33.728899+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/IOUUATSROJZ7RI43R2C7V4DMJ5","json":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5.json","graph_json":"https://pith.science/api/pith-number/IOUUATSROJZ7RI43R2C7V4DMJ5/graph.json","events_json":"https://pith.science/api/pith-number/IOUUATSROJZ7RI43R2C7V4DMJ5/events.json","paper":"https://pith.science/paper/IOUUATSR"},"agent_actions":{"view_html":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5","download_json":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5.json","view_paper":"https://pith.science/paper/IOUUATSR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2602.06989&json=true","fetch_graph":"https://pith.science/api/pith-number/IOUUATSROJZ7RI43R2C7V4DMJ5/graph.json","fetch_events":"https://pith.science/api/pith-number/IOUUATSROJZ7RI43R2C7V4DMJ5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5/action/storage_attestation","attest_author":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5/action/author_attestation","sign_citation":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5/action/citation_signature","submit_replication":"https://pith.science/pith/IOUUATSROJZ7RI43R2C7V4DMJ5/action/replication_record"}},"created_at":"2026-06-30T01:17:33.728899+00:00","updated_at":"2026-06-30T01:17:33.728899+00:00"}