{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:X35C3TSOCBRFY3E7CBEGQV7YJV","short_pith_number":"pith:X35C3TSO","schema_version":"1.0","canonical_sha256":"befa2dce4e10625c6c9f10486857f84d5c113beb2f0d6e3608aafd6926808dc8","source":{"kind":"arxiv","id":"2607.17162","version":1},"attestation_state":"computed","paper":{"title":"XMatcher: An Open-Source Framework for X-Ray Diffraction Phase Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Bin Cao","submitted_at":"2026-07-19T09:45:29Z","abstract_excerpt":"Powder X-ray diffraction (XRD) is widely used for crystalline phase identification, and recent machine learning approaches have demonstrated remarkable capabilities in accelerating diffraction interpretation. However, reliable phase assignment still requires transparent, evidence-based validation, particularly for complex samples where interpretability and expert assessment remain essential. Search-match methods provide a robust and complementary strategy, yet many implementations are proprietary, limiting accessibility and reproducibility. Here, we introduce XMatcher, an open-source, evidence"},"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":"2607.17162","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2026-07-19T09:45:29Z","cross_cats_sorted":[],"title_canon_sha256":"b583d5c56f60bed8a5c54407339c61ef155d282641ec06019d6f28c45c030a1f","abstract_canon_sha256":"faa84af9c2dbc00bd0a16f63919d2eec1801a96af5394159fafe031e711cc9de"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:21:18.716739Z","signature_b64":"9mIvk0g/gped4QXyZjHQSQO2FTuxG1VrdsUY0rZQXFv5Dq17Z/+Z+T5umsndIpZ1bO6BQCv/gJgdcbN0E5zdDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"befa2dce4e10625c6c9f10486857f84d5c113beb2f0d6e3608aafd6926808dc8","last_reissued_at":"2026-07-21T01:21:18.715777Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:21:18.715777Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"XMatcher: An Open-Source Framework for X-Ray Diffraction Phase Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Bin Cao","submitted_at":"2026-07-19T09:45:29Z","abstract_excerpt":"Powder X-ray diffraction (XRD) is widely used for crystalline phase identification, and recent machine learning approaches have demonstrated remarkable capabilities in accelerating diffraction interpretation. However, reliable phase assignment still requires transparent, evidence-based validation, particularly for complex samples where interpretability and expert assessment remain essential. Search-match methods provide a robust and complementary strategy, yet many implementations are proprietary, limiting accessibility and reproducibility. Here, we introduce XMatcher, an open-source, evidence"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17162","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/2607.17162/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":"2607.17162","created_at":"2026-07-21T01:21:18.716219+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.17162v1","created_at":"2026-07-21T01:21:18.716219+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17162","created_at":"2026-07-21T01:21:18.716219+00:00"},{"alias_kind":"pith_short_12","alias_value":"X35C3TSOCBRF","created_at":"2026-07-21T01:21:18.716219+00:00"},{"alias_kind":"pith_short_16","alias_value":"X35C3TSOCBRFY3E7","created_at":"2026-07-21T01:21:18.716219+00:00"},{"alias_kind":"pith_short_8","alias_value":"X35C3TSO","created_at":"2026-07-21T01:21:18.716219+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/X35C3TSOCBRFY3E7CBEGQV7YJV","json":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV.json","graph_json":"https://pith.science/api/pith-number/X35C3TSOCBRFY3E7CBEGQV7YJV/graph.json","events_json":"https://pith.science/api/pith-number/X35C3TSOCBRFY3E7CBEGQV7YJV/events.json","paper":"https://pith.science/paper/X35C3TSO"},"agent_actions":{"view_html":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV","download_json":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV.json","view_paper":"https://pith.science/paper/X35C3TSO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.17162&json=true","fetch_graph":"https://pith.science/api/pith-number/X35C3TSOCBRFY3E7CBEGQV7YJV/graph.json","fetch_events":"https://pith.science/api/pith-number/X35C3TSOCBRFY3E7CBEGQV7YJV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV/action/storage_attestation","attest_author":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV/action/author_attestation","sign_citation":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV/action/citation_signature","submit_replication":"https://pith.science/pith/X35C3TSOCBRFY3E7CBEGQV7YJV/action/replication_record"}},"created_at":"2026-07-21T01:21:18.716219+00:00","updated_at":"2026-07-21T01:21:18.716219+00:00"}