{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:PUVMMSJWWC4O6OT6YDQ2N7NSSU","short_pith_number":"pith:PUVMMSJW","schema_version":"1.0","canonical_sha256":"7d2ac64936b0b8ef3a7ec0e1a6fdb29500c8589fd0801cc908e352084821befa","source":{"kind":"arxiv","id":"2606.00302","version":1},"attestation_state":"computed","paper":{"title":"ERICA: Quantifying Replicability of Cluster Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Manuel A. Rivas, Robert Tibshirani, Siamak K. Sorooshyari","submitted_at":"2026-05-29T19:31:26Z","abstract_excerpt":"Despite being ubiquitous in science, clustering remains a technique whose results are not quantitatively scrutinized via a framework. We present an analysis called evaluating replicability via iterative clustering assignments (ERICA) that is applied to a dataset to determine whether clusters are identified in a replicable manner. The pipeline computes a statistic that describes whether structure is found in a dataset. Quantitative visualization methods are presented to answer important questions such as the similarity between clusters, and the identity of points that may be outliers. When test"},"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":"2606.00302","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-05-29T19:31:26Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f573c7c71327dd6e3983238bd1996e317d94bdff8b18b2745a6b81cf4e9d0b60","abstract_canon_sha256":"12aebd9fe151c44a998563e84aa30421a6dc6485fbc68ff89d35d3c421bb0c1e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:03:51.108307Z","signature_b64":"82sJIDrEavUteNjClT2Q03Ge0LYKdoOoH70qTspJdiL2gKlox41GAl3LqzGAPtpD3wp8E1KC1vfpMBJMcyZwCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7d2ac64936b0b8ef3a7ec0e1a6fdb29500c8589fd0801cc908e352084821befa","last_reissued_at":"2026-06-02T01:03:51.107896Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:03:51.107896Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ERICA: Quantifying Replicability of Cluster Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Manuel A. Rivas, Robert Tibshirani, Siamak K. Sorooshyari","submitted_at":"2026-05-29T19:31:26Z","abstract_excerpt":"Despite being ubiquitous in science, clustering remains a technique whose results are not quantitatively scrutinized via a framework. We present an analysis called evaluating replicability via iterative clustering assignments (ERICA) that is applied to a dataset to determine whether clusters are identified in a replicable manner. The pipeline computes a statistic that describes whether structure is found in a dataset. Quantitative visualization methods are presented to answer important questions such as the similarity between clusters, and the identity of points that may be outliers. When test"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.00302","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.00302/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":"2606.00302","created_at":"2026-06-02T01:03:51.107963+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.00302v1","created_at":"2026-06-02T01:03:51.107963+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.00302","created_at":"2026-06-02T01:03:51.107963+00:00"},{"alias_kind":"pith_short_12","alias_value":"PUVMMSJWWC4O","created_at":"2026-06-02T01:03:51.107963+00:00"},{"alias_kind":"pith_short_16","alias_value":"PUVMMSJWWC4O6OT6","created_at":"2026-06-02T01:03:51.107963+00:00"},{"alias_kind":"pith_short_8","alias_value":"PUVMMSJW","created_at":"2026-06-02T01:03:51.107963+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/PUVMMSJWWC4O6OT6YDQ2N7NSSU","json":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU.json","graph_json":"https://pith.science/api/pith-number/PUVMMSJWWC4O6OT6YDQ2N7NSSU/graph.json","events_json":"https://pith.science/api/pith-number/PUVMMSJWWC4O6OT6YDQ2N7NSSU/events.json","paper":"https://pith.science/paper/PUVMMSJW"},"agent_actions":{"view_html":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU","download_json":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU.json","view_paper":"https://pith.science/paper/PUVMMSJW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.00302&json=true","fetch_graph":"https://pith.science/api/pith-number/PUVMMSJWWC4O6OT6YDQ2N7NSSU/graph.json","fetch_events":"https://pith.science/api/pith-number/PUVMMSJWWC4O6OT6YDQ2N7NSSU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU/action/storage_attestation","attest_author":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU/action/author_attestation","sign_citation":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU/action/citation_signature","submit_replication":"https://pith.science/pith/PUVMMSJWWC4O6OT6YDQ2N7NSSU/action/replication_record"}},"created_at":"2026-06-02T01:03:51.107963+00:00","updated_at":"2026-06-02T01:03:51.107963+00:00"}