{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:2V7ORJ7MLJLKAXM7PUNHYIRGN2","short_pith_number":"pith:2V7ORJ7M","schema_version":"1.0","canonical_sha256":"d57ee8a7ec5a56a05d9f7d1a7c22266ebc2912e6b7154c1894bef3f4dad2f24c","source":{"kind":"arxiv","id":"1609.02818","version":2},"attestation_state":"computed","paper":{"title":"Network Psychometrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Denny Borsboom, Gunter K. J. Maris, Lourens J. Waldorp, Sacha Epskamp","submitted_at":"2016-09-09T14:51:54Z","abstract_excerpt":"This chapter provides a general introduction of network modeling in psychometrics. The chapter starts with an introduction to the statistical model formulation of pairwise Markov random fields (PMRF), followed by an introduction of the PMRF suitable for binary data: the Ising model. The Ising model is a model used in ferromagnetism to explain phase transitions in a field of particles. Following the description of the Ising model in statistical physics, the chapter continues to show that the Ising model is closely related to models used in psychometrics. The Ising model can be shown to be equiv"},"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":"1609.02818","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-09-09T14:51:54Z","cross_cats_sorted":[],"title_canon_sha256":"8a6b6d5df7f4b2febd763a5f27dc67df50536a3c2b32f82ddeb2014e0b48594c","abstract_canon_sha256":"62865538eb49d7684f1d89ebdfc28682acf34fc7ba70cafc032ee7b47f1f4d2a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:01.465069Z","signature_b64":"i9tG/K9wggGIeyMtgo0dRyT0GmohB2wu9FKvcNl1TEuPRk+r0hnM8gcBVdkptnIh0WCoeAnaelT0Po5d7ZFHBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d57ee8a7ec5a56a05d9f7d1a7c22266ebc2912e6b7154c1894bef3f4dad2f24c","last_reissued_at":"2026-05-18T00:14:01.464489Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:01.464489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Network Psychometrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Denny Borsboom, Gunter K. J. Maris, Lourens J. Waldorp, Sacha Epskamp","submitted_at":"2016-09-09T14:51:54Z","abstract_excerpt":"This chapter provides a general introduction of network modeling in psychometrics. The chapter starts with an introduction to the statistical model formulation of pairwise Markov random fields (PMRF), followed by an introduction of the PMRF suitable for binary data: the Ising model. The Ising model is a model used in ferromagnetism to explain phase transitions in a field of particles. Following the description of the Ising model in statistical physics, the chapter continues to show that the Ising model is closely related to models used in psychometrics. The Ising model can be shown to be equiv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1609.02818","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1609.02818","created_at":"2026-05-18T00:14:01.464587+00:00"},{"alias_kind":"arxiv_version","alias_value":"1609.02818v2","created_at":"2026-05-18T00:14:01.464587+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1609.02818","created_at":"2026-05-18T00:14:01.464587+00:00"},{"alias_kind":"pith_short_12","alias_value":"2V7ORJ7MLJLK","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_16","alias_value":"2V7ORJ7MLJLKAXM7","created_at":"2026-05-18T12:29:55.572404+00:00"},{"alias_kind":"pith_short_8","alias_value":"2V7ORJ7M","created_at":"2026-05-18T12:29:55.572404+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/2V7ORJ7MLJLKAXM7PUNHYIRGN2","json":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2.json","graph_json":"https://pith.science/api/pith-number/2V7ORJ7MLJLKAXM7PUNHYIRGN2/graph.json","events_json":"https://pith.science/api/pith-number/2V7ORJ7MLJLKAXM7PUNHYIRGN2/events.json","paper":"https://pith.science/paper/2V7ORJ7M"},"agent_actions":{"view_html":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2","download_json":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2.json","view_paper":"https://pith.science/paper/2V7ORJ7M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1609.02818&json=true","fetch_graph":"https://pith.science/api/pith-number/2V7ORJ7MLJLKAXM7PUNHYIRGN2/graph.json","fetch_events":"https://pith.science/api/pith-number/2V7ORJ7MLJLKAXM7PUNHYIRGN2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2/action/storage_attestation","attest_author":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2/action/author_attestation","sign_citation":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2/action/citation_signature","submit_replication":"https://pith.science/pith/2V7ORJ7MLJLKAXM7PUNHYIRGN2/action/replication_record"}},"created_at":"2026-05-18T00:14:01.464587+00:00","updated_at":"2026-05-18T00:14:01.464587+00:00"}