{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DGF3VOVJRM5MU56BRTUXZOLTBG","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":"47821c7407169611fef0a1d222614ce58352b3778f19fb5b2c411e9522812caf","cross_cats_sorted":["cs.LG","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-06-03T16:09:15Z","title_canon_sha256":"a7753008c847242005222cec9fd9ceba91f66d1a111a4afdbdc93b412e1a5e03"},"schema_version":"1.0","source":{"id":"2606.05258","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05258","created_at":"2026-06-05T00:13:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05258v1","created_at":"2026-06-05T00:13:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05258","created_at":"2026-06-05T00:13:50Z"},{"alias_kind":"pith_short_12","alias_value":"DGF3VOVJRM5M","created_at":"2026-06-05T00:13:50Z"},{"alias_kind":"pith_short_16","alias_value":"DGF3VOVJRM5MU56B","created_at":"2026-06-05T00:13:50Z"},{"alias_kind":"pith_short_8","alias_value":"DGF3VOVJ","created_at":"2026-06-05T00:13:50Z"}],"graph_snapshots":[{"event_id":"sha256:69eaa997b783e81c04becd9e7705973c1519b6cdd858e8506ce74f73e23fab43","target":"graph","created_at":"2026-06-05T00:13:50Z","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/2606.05258/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transfer learning is a natural strategy when a target population has limited data but multiple related auxiliary sources are available. A central difficulty is source heterogeneity: auxiliary sources may not be equally useful, and their usefulness may vary in a structured, cluster-like fashion. Existing transfer-learning methods often reduce source selection to a binary informative/non-informative decision, overlooking subgroups of sources with differential transferability. Motivated by a suicide-risk study using data from the Connecticut Hospital Information Management Exchange (CHIME), compr","authors_text":"Jun Jin, Kun Chen, Robert H. Aseltine, Shane J. Sacco, Xiaohui Yin","cross_cats":["cs.LG","stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-06-03T16:09:15Z","title":"Harnessing Source Heterogeneity for Cluster-Structured Transfer Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05258","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":"sha256:78a1e5f204b8e2b9579a160722e839875499ccf9b00eb870486e77b243f30258","target":"record","created_at":"2026-06-05T00:13:50Z","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":"47821c7407169611fef0a1d222614ce58352b3778f19fb5b2c411e9522812caf","cross_cats_sorted":["cs.LG","stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2026-06-03T16:09:15Z","title_canon_sha256":"a7753008c847242005222cec9fd9ceba91f66d1a111a4afdbdc93b412e1a5e03"},"schema_version":"1.0","source":{"id":"2606.05258","kind":"arxiv","version":1}},"canonical_sha256":"198bbabaa98b3aca77c18ce97cb97309b3a2062585351638f534060004ce0d7e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"198bbabaa98b3aca77c18ce97cb97309b3a2062585351638f534060004ce0d7e","first_computed_at":"2026-06-05T00:13:50.740048Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T00:13:50.740048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wm7wQJadm6Za7PpknbGCHHq+NqiW+4+5uu2CRBfR5xJHc7qfMk+OJhm1s9pPCh6FqI86BLk8KBmnOT+H1gxtCA==","signature_status":"signed_v1","signed_at":"2026-06-05T00:13:50.740475Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05258","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:78a1e5f204b8e2b9579a160722e839875499ccf9b00eb870486e77b243f30258","sha256:69eaa997b783e81c04becd9e7705973c1519b6cdd858e8506ce74f73e23fab43"],"state_sha256":"601790584d2279d0647e5ef08572dbc35f296e746b45c0c6ffea52ee251ac686"}