{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:NTHZRIXWLBR5TH4P6JLUVT7Z7L","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":"4e661ae62a93333e7825fabd910d067249678e9685e26601ecef3e5d7c15ad73","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2022-03-10T07:16:29Z","title_canon_sha256":"d549b9c98053bfc53cb006b424b04f960bc16d80fae84b5afc3b0cf6616673b9"},"schema_version":"1.0","source":{"id":"2203.05197","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.05197","created_at":"2026-07-05T10:05:05Z"},{"alias_kind":"arxiv_version","alias_value":"2203.05197v4","created_at":"2026-07-05T10:05:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.05197","created_at":"2026-07-05T10:05:05Z"},{"alias_kind":"pith_short_12","alias_value":"NTHZRIXWLBR5","created_at":"2026-07-05T10:05:05Z"},{"alias_kind":"pith_short_16","alias_value":"NTHZRIXWLBR5TH4P","created_at":"2026-07-05T10:05:05Z"},{"alias_kind":"pith_short_8","alias_value":"NTHZRIXW","created_at":"2026-07-05T10:05:05Z"}],"graph_snapshots":[{"event_id":"sha256:02670ff612a006934073b90aff775dfdde250ccb598144f063ca636a7ecd36bb","target":"graph","created_at":"2026-07-05T10:05:05Z","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/2203.05197/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Due to spatial dependence -- often characterized as complex and non-linear -- model misspecification is a prevalent and critical issue in spatial data analysis and prediction. As the data, and thus model performance, is heterogeneous, typical model selection and ensemble methods that assume homogeneity are not suitable. We address the issue of model uncertainty for spatial data by proposing a novel Bayesian ensemble methodology that captures spatially-varying model uncertainty and performance heterogeneity of multiple spatial predictions, and synthesizes them for improved predictions, which we","authors_text":"Danielle Cabel, Kenichiro McAlinn, Kosaku Takanashi, Masahiro Kato, Shonosuke Sugasawa","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2022-03-10T07:16:29Z","title":"Bayesian Spatial Predictive Synthesis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.05197","kind":"arxiv","version":4},"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":"sha256:4fd3dfb158d43bb9b2c783648900a21a4f8183a7225c8c91475b2cdddf97b15a","target":"record","created_at":"2026-07-05T10:05:05Z","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":"4e661ae62a93333e7825fabd910d067249678e9685e26601ecef3e5d7c15ad73","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2022-03-10T07:16:29Z","title_canon_sha256":"d549b9c98053bfc53cb006b424b04f960bc16d80fae84b5afc3b0cf6616673b9"},"schema_version":"1.0","source":{"id":"2203.05197","kind":"arxiv","version":4}},"canonical_sha256":"6ccf98a2f65863d99f8ff2574acff9faee654e0f404dae86122f0b2be9f051be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ccf98a2f65863d99f8ff2574acff9faee654e0f404dae86122f0b2be9f051be","first_computed_at":"2026-07-05T10:05:05.739086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:05:05.739086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vft7Qj1XaDdwQNLW+8dynu5jfeJBrxvCPrm3oDrwqI8TzO3HGC6+WhaCPdMrdav2CZzoRyBgMsR+KTfyUErSBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:05:05.739508Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.05197","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4fd3dfb158d43bb9b2c783648900a21a4f8183a7225c8c91475b2cdddf97b15a","sha256:02670ff612a006934073b90aff775dfdde250ccb598144f063ca636a7ecd36bb"],"state_sha256":"3e8c5a9a9c8718e504082877004c342aa57dbc2349148a8a6abd23a0c38066df"}