{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:6VEW5QTMVZQAGSWCBVX74B6WHI","short_pith_number":"pith:6VEW5QTM","canonical_record":{"source":{"id":"1802.06359","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-02-18T10:19:53Z","cross_cats_sorted":[],"title_canon_sha256":"b0d9ec03e4298d6b40046a351d67b0f56282265a1cfd7321f8d9363d74c568c7","abstract_canon_sha256":"3ad49af90bb954e38dd2c3b0c75d8b980ff9d7b896e3accdc8ca830351efdafd"},"schema_version":"1.0"},"canonical_sha256":"f5496ec26cae60034ac20d6ffe07d63a1e37a3d48b94d3c21e8e29dd5f78e39c","source":{"kind":"arxiv","id":"1802.06359","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.06359","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"arxiv_version","alias_value":"1802.06359v1","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.06359","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"pith_short_12","alias_value":"6VEW5QTMVZQA","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"6VEW5QTMVZQAGSWC","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"6VEW5QTM","created_at":"2026-05-18T12:32:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:6VEW5QTMVZQAGSWCBVX74B6WHI","target":"record","payload":{"canonical_record":{"source":{"id":"1802.06359","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-02-18T10:19:53Z","cross_cats_sorted":[],"title_canon_sha256":"b0d9ec03e4298d6b40046a351d67b0f56282265a1cfd7321f8d9363d74c568c7","abstract_canon_sha256":"3ad49af90bb954e38dd2c3b0c75d8b980ff9d7b896e3accdc8ca830351efdafd"},"schema_version":"1.0"},"canonical_sha256":"f5496ec26cae60034ac20d6ffe07d63a1e37a3d48b94d3c21e8e29dd5f78e39c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:03.501695Z","signature_b64":"7ie+nnhUcPMV4oK9d6OXM0khcScX66NfOnD+7p3MKSJTIkT4DIhrhZ9wrHKq+XJqo7KLhsObKhthrBttohogDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5496ec26cae60034ac20d6ffe07d63a1e37a3d48b94d3c21e8e29dd5f78e39c","last_reissued_at":"2026-05-18T00:23:03.501072Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:03.501072Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.06359","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":"2026-05-18T00:23:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+DpF+r2dAuP87p1m6oV9O6mPir26JEpifjDoCtnIdJIPrARy28hPFrF8SV+mqVI/2LtrWYiAzSc2bhE6G/4sCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:19:50.134035Z"},"content_sha256":"e3ef305b4cc6b5dc4f15fdbdf265faaf1d1832571fc6f46b786d8a1b00f98c26","schema_version":"1.0","event_id":"sha256:e3ef305b4cc6b5dc4f15fdbdf265faaf1d1832571fc6f46b786d8a1b00f98c26"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:6VEW5QTMVZQAGSWCBVX74B6WHI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Abdisalan M. Noor, Emanuele Giorgi, Peter J. Diggle, Robert W. Snow","submitted_at":"2018-02-18T10:19:53Z","abstract_excerpt":"In this paper we set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to provide a tutorial guide that can be used in order to identify parsimonious geostatistical models for prevalence mapping. A general variogram-based Monte Carlo procedure is proposed to check the validity of the modelling assumptions. We describe and contrast likelihood-based and Bayesian methods of inference, showing how to account for parameter uncertainty under each of the two paradigms. We also describe extensions o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.06359","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":"2026-05-18T00:23:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OZY/b7bkKGZJZnvHypcBkuKyelXXvc/MGEh0uIW3VpyWQm0uNIPyoMykKpv5tlcG0LjVPJyyaDUomZDF1UIlDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T12:19:50.134770Z"},"content_sha256":"c8bb4b8791432ce01ff54a320319e3190ac97def6f4483cbaac7715aa49d31e6","schema_version":"1.0","event_id":"sha256:c8bb4b8791432ce01ff54a320319e3190ac97def6f4483cbaac7715aa49d31e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/bundle.json","state_url":"https://pith.science/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/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":"2026-05-26T12:19:50Z","links":{"resolver":"https://pith.science/pith/6VEW5QTMVZQAGSWCBVX74B6WHI","bundle":"https://pith.science/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/bundle.json","state":"https://pith.science/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6VEW5QTMVZQAGSWCBVX74B6WHI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:6VEW5QTMVZQAGSWCBVX74B6WHI","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":"3ad49af90bb954e38dd2c3b0c75d8b980ff9d7b896e3accdc8ca830351efdafd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-02-18T10:19:53Z","title_canon_sha256":"b0d9ec03e4298d6b40046a351d67b0f56282265a1cfd7321f8d9363d74c568c7"},"schema_version":"1.0","source":{"id":"1802.06359","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.06359","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"arxiv_version","alias_value":"1802.06359v1","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.06359","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"pith_short_12","alias_value":"6VEW5QTMVZQA","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_16","alias_value":"6VEW5QTMVZQAGSWC","created_at":"2026-05-18T12:32:11Z"},{"alias_kind":"pith_short_8","alias_value":"6VEW5QTM","created_at":"2026-05-18T12:32:11Z"}],"graph_snapshots":[{"event_id":"sha256:c8bb4b8791432ce01ff54a320319e3190ac97def6f4483cbaac7715aa49d31e6","target":"graph","created_at":"2026-05-18T00:23:03Z","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 set out general principles and develop geostatistical methods for the analysis of data from spatio-temporally referenced prevalence surveys. Our objective is to provide a tutorial guide that can be used in order to identify parsimonious geostatistical models for prevalence mapping. A general variogram-based Monte Carlo procedure is proposed to check the validity of the modelling assumptions. We describe and contrast likelihood-based and Bayesian methods of inference, showing how to account for parameter uncertainty under each of the two paradigms. We also describe extensions o","authors_text":"Abdisalan M. Noor, Emanuele Giorgi, Peter J. Diggle, Robert W. Snow","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-02-18T10:19:53Z","title":"Geostatistical methods for disease mapping and visualization using data from spatio-temporally referenced prevalence surveys"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.06359","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:e3ef305b4cc6b5dc4f15fdbdf265faaf1d1832571fc6f46b786d8a1b00f98c26","target":"record","created_at":"2026-05-18T00:23:03Z","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":"3ad49af90bb954e38dd2c3b0c75d8b980ff9d7b896e3accdc8ca830351efdafd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-02-18T10:19:53Z","title_canon_sha256":"b0d9ec03e4298d6b40046a351d67b0f56282265a1cfd7321f8d9363d74c568c7"},"schema_version":"1.0","source":{"id":"1802.06359","kind":"arxiv","version":1}},"canonical_sha256":"f5496ec26cae60034ac20d6ffe07d63a1e37a3d48b94d3c21e8e29dd5f78e39c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f5496ec26cae60034ac20d6ffe07d63a1e37a3d48b94d3c21e8e29dd5f78e39c","first_computed_at":"2026-05-18T00:23:03.501072Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:03.501072Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7ie+nnhUcPMV4oK9d6OXM0khcScX66NfOnD+7p3MKSJTIkT4DIhrhZ9wrHKq+XJqo7KLhsObKhthrBttohogDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:03.501695Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.06359","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3ef305b4cc6b5dc4f15fdbdf265faaf1d1832571fc6f46b786d8a1b00f98c26","sha256:c8bb4b8791432ce01ff54a320319e3190ac97def6f4483cbaac7715aa49d31e6"],"state_sha256":"69d080efb765d6f88bece32afb57a2d79eaca9d179cc66939a50f464850f6230"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AlPZza0IFaSbq9E8Z7+D0527Kd/Uuewk/Dw69lqYcfa2MiAbIzHeMq6gQ9++Utup6uTFnYsm+z5Qxt99Job1CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T12:19:50.138405Z","bundle_sha256":"e946ef550e76d7401236485f812118e09279b07f8db5590c1ffcd7d42fb4bfcd"}}