{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WCQP2XWGEFTPHDSIGPSCEPKWKI","short_pith_number":"pith:WCQP2XWG","canonical_record":{"source":{"id":"1805.08590","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-05-22T14:09:04Z","cross_cats_sorted":[],"title_canon_sha256":"3ad87d361e3c935c79497edd576108942cb255cc431f66dd1be8dcfa7c124b88","abstract_canon_sha256":"7d35ea491c42b17e311446bfc2d6dee68cd748856cc439a8fc2d97520a9c4bbf"},"schema_version":"1.0"},"canonical_sha256":"b0a0fd5ec62166f38e4833e4223d5652231cf4e0a48570c8aaa7b6661e91c644","source":{"kind":"arxiv","id":"1805.08590","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08590","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08590v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08590","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"WCQP2XWGEFTP","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WCQP2XWGEFTPHDSI","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WCQP2XWG","created_at":"2026-05-18T12:32:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WCQP2XWGEFTPHDSIGPSCEPKWKI","target":"record","payload":{"canonical_record":{"source":{"id":"1805.08590","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-05-22T14:09:04Z","cross_cats_sorted":[],"title_canon_sha256":"3ad87d361e3c935c79497edd576108942cb255cc431f66dd1be8dcfa7c124b88","abstract_canon_sha256":"7d35ea491c42b17e311446bfc2d6dee68cd748856cc439a8fc2d97520a9c4bbf"},"schema_version":"1.0"},"canonical_sha256":"b0a0fd5ec62166f38e4833e4223d5652231cf4e0a48570c8aaa7b6661e91c644","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:25.857917Z","signature_b64":"FTHxh6PA5ZCCfM+2/CtEEmCQP/1eb+xBdIjgVXjSzUnUH9A1Nibjo7gOo/PAtGV5VSlIHiv/JzlSpsL7HBI5DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0a0fd5ec62166f38e4833e4223d5652231cf4e0a48570c8aaa7b6661e91c644","last_reissued_at":"2026-05-18T00:15:25.857258Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:25.857258Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.08590","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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nH7KwaHqjSUJE0G6uy9VAL5TBl5iD5fh0e4YnkQjm53kPrebS/L2gVTtrVq3HQPt/Vj2ap/8s3UeJx9uyYvpBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T23:30:24.159790Z"},"content_sha256":"b7a9318096413a6236be34b585eb6e6a1a3395086c36cb91f2d5252e998fd6fb","schema_version":"1.0","event_id":"sha256:b7a9318096413a6236be34b585eb6e6a1a3395086c36cb91f2d5252e998fd6fb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WCQP2XWGEFTPHDSIGPSCEPKWKI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Empirical Bayes Approach for Distributed Estimation of Spatial Fields","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.SY","authors_text":"Angelo Coluccia, Francesco Sasso, Giuseppe Notarstefano","submitted_at":"2018-05-22T14:09:04Z","abstract_excerpt":"In this paper we consider a network of spatially distributed sensors which collect measurement samples of a spatial field, and aim at estimating in a distributed way (without any central coordinator) the entire field by suitably fusing all network data. We propose a general probabilistic model that can handle both partial knowledge of the physics generating the spatial field as well as a purely data-driven inference. Specifically, we adopt an Empirical Bayes approach in which the spatial field is modeled as a Gaussian Process, whose mean function is described by means of parametrized equations"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08590","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":""},"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":"2026-05-18T00:15:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SNhtXkoe2+UfbUd4yRUYDZyRRLeajJhILMtnYocoqMGj2t6eKYul8qOzrLX/lpIPTx5OfzWyXEMR3o1ONowYBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T23:30:24.160134Z"},"content_sha256":"caa393a7cc8065c67548056bbf0b546ac3500f38a5394f0868bddb688e5f590c","schema_version":"1.0","event_id":"sha256:caa393a7cc8065c67548056bbf0b546ac3500f38a5394f0868bddb688e5f590c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/bundle.json","state_url":"https://pith.science/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/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":"2026-06-01T23:30:24Z","links":{"resolver":"https://pith.science/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI","bundle":"https://pith.science/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/bundle.json","state":"https://pith.science/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WCQP2XWGEFTPHDSIGPSCEPKWKI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WCQP2XWGEFTPHDSIGPSCEPKWKI","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":"7d35ea491c42b17e311446bfc2d6dee68cd748856cc439a8fc2d97520a9c4bbf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-05-22T14:09:04Z","title_canon_sha256":"3ad87d361e3c935c79497edd576108942cb255cc431f66dd1be8dcfa7c124b88"},"schema_version":"1.0","source":{"id":"1805.08590","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.08590","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"arxiv_version","alias_value":"1805.08590v1","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.08590","created_at":"2026-05-18T00:15:25Z"},{"alias_kind":"pith_short_12","alias_value":"WCQP2XWGEFTP","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WCQP2XWGEFTPHDSI","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WCQP2XWG","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:caa393a7cc8065c67548056bbf0b546ac3500f38a5394f0868bddb688e5f590c","target":"graph","created_at":"2026-05-18T00:15:25Z","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"},"paper":{"abstract_excerpt":"In this paper we consider a network of spatially distributed sensors which collect measurement samples of a spatial field, and aim at estimating in a distributed way (without any central coordinator) the entire field by suitably fusing all network data. We propose a general probabilistic model that can handle both partial knowledge of the physics generating the spatial field as well as a purely data-driven inference. Specifically, we adopt an Empirical Bayes approach in which the spatial field is modeled as a Gaussian Process, whose mean function is described by means of parametrized equations","authors_text":"Angelo Coluccia, Francesco Sasso, Giuseppe Notarstefano","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-05-22T14:09:04Z","title":"An Empirical Bayes Approach for Distributed Estimation of Spatial Fields"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.08590","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:b7a9318096413a6236be34b585eb6e6a1a3395086c36cb91f2d5252e998fd6fb","target":"record","created_at":"2026-05-18T00:15:25Z","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":"7d35ea491c42b17e311446bfc2d6dee68cd748856cc439a8fc2d97520a9c4bbf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-05-22T14:09:04Z","title_canon_sha256":"3ad87d361e3c935c79497edd576108942cb255cc431f66dd1be8dcfa7c124b88"},"schema_version":"1.0","source":{"id":"1805.08590","kind":"arxiv","version":1}},"canonical_sha256":"b0a0fd5ec62166f38e4833e4223d5652231cf4e0a48570c8aaa7b6661e91c644","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0a0fd5ec62166f38e4833e4223d5652231cf4e0a48570c8aaa7b6661e91c644","first_computed_at":"2026-05-18T00:15:25.857258Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:15:25.857258Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FTHxh6PA5ZCCfM+2/CtEEmCQP/1eb+xBdIjgVXjSzUnUH9A1Nibjo7gOo/PAtGV5VSlIHiv/JzlSpsL7HBI5DQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:15:25.857917Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.08590","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b7a9318096413a6236be34b585eb6e6a1a3395086c36cb91f2d5252e998fd6fb","sha256:caa393a7cc8065c67548056bbf0b546ac3500f38a5394f0868bddb688e5f590c"],"state_sha256":"ca5a5db63db5daaa461dbb5eb92ab4d82751183ac531fc5300730b5525bdc140"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QPY9rN8GaW0uftNEdszYm3qLYMzLDHBJuE3TGlSyM5JqyPDMNkgmNWD/ck0BjF4KWyd7u+KpxLMD1Ev3MG5aDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T23:30:24.162197Z","bundle_sha256":"976af403fafe92fb50f443f98574254fdcafd5b32cf96d91f1556c14ccd646b5"}}