{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4REFAHMLT3VIXG4LEMLNEJEVAZ","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":"af7372121c5300ab25edcacdc763c15fafe9f36ade8c9225e9d035ad0d8fb22f","cross_cats_sorted":["cs.IR","econ.GN","q-fin.EC","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-01T21:03:04Z","title_canon_sha256":"5dcef5f35c40293df4694df520f767f5e5fe03819ce1b41d0c3580846781243a"},"schema_version":"1.0","source":{"id":"2407.02536","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.02536","created_at":"2026-07-05T08:39:38Z"},{"alias_kind":"arxiv_version","alias_value":"2407.02536v1","created_at":"2026-07-05T08:39:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.02536","created_at":"2026-07-05T08:39:38Z"},{"alias_kind":"pith_short_12","alias_value":"4REFAHMLT3VI","created_at":"2026-07-05T08:39:38Z"},{"alias_kind":"pith_short_16","alias_value":"4REFAHMLT3VIXG4L","created_at":"2026-07-05T08:39:38Z"},{"alias_kind":"pith_short_8","alias_value":"4REFAHML","created_at":"2026-07-05T08:39:38Z"}],"graph_snapshots":[{"event_id":"sha256:22a29865c5b7c5213bd10dd9a52b0c76fbeadd460b09832640b17c91b13b4787","target":"graph","created_at":"2026-07-05T08:39:38Z","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/2407.02536/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Given a set \\emph{S} of spatial feature types, its feature instances, a study area, and a neighbor relationship, the goal is to find pairs $<$a region ($r_{g}$), a subset \\emph{C} of \\emph{S}$>$ such that \\emph{C} is a statistically significant regional-colocation pattern in $r_{g}$. This problem is important for applications in various domains including ecology, economics, and sociology. The problem is computationally challenging due to the exponential number of regional colocation patterns and candidate regions. Previously, we proposed a miner \\cite{10.1145/3557989.3566158} that finds statis","authors_text":"Arun Sharma, Jayant Gupta, Shashi Shekhar, Shuai An, Subhankar Ghosh","cross_cats":["cs.IR","econ.GN","q-fin.EC","stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-01T21:03:04Z","title":"Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.02536","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":"sha256:3d2fb75a004e266fca588c17264b71c944275b28678b6445bc55b3ebc36e6115","target":"record","created_at":"2026-07-05T08:39:38Z","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":"af7372121c5300ab25edcacdc763c15fafe9f36ade8c9225e9d035ad0d8fb22f","cross_cats_sorted":["cs.IR","econ.GN","q-fin.EC","stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-07-01T21:03:04Z","title_canon_sha256":"5dcef5f35c40293df4694df520f767f5e5fe03819ce1b41d0c3580846781243a"},"schema_version":"1.0","source":{"id":"2407.02536","kind":"arxiv","version":1}},"canonical_sha256":"e448501d8b9eea8b9b8b2316d2249506696d792d33c578daa097d8038773294a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e448501d8b9eea8b9b8b2316d2249506696d792d33c578daa097d8038773294a","first_computed_at":"2026-07-05T08:39:38.028060Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:39:38.028060Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+uwciA59Pp1OsmVhvMlLwPVdLjv50KvcTVDh6IpPSxHbbbx+ff/1BdNis/qjF3mSI415z4DIe0j7IxEGamjuAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:39:38.028414Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.02536","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d2fb75a004e266fca588c17264b71c944275b28678b6445bc55b3ebc36e6115","sha256:22a29865c5b7c5213bd10dd9a52b0c76fbeadd460b09832640b17c91b13b4787"],"state_sha256":"924c999a21c69164e9b0f104192c07e6f86a9b38f6f5dc1b87974c6be8da025a"}