{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:ORDURJMLM3UPXT27WB3KMYEFOD","short_pith_number":"pith:ORDURJML","schema_version":"1.0","canonical_sha256":"744748a58b66e8fbcf5fb076a6608570eef7f542b2dd21aafb1590db4ad24efc","source":{"kind":"arxiv","id":"1212.2007","version":1},"attestation_state":"computed","paper":{"title":"Empirical physical formula for potential energy curves of 38-66Ti isotopes by using neural networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"nucl-th","authors_text":"N. Yildiz, S. Akkoyun, S. O. Kara, T. Bayram","submitted_at":"2012-12-10T09:41:43Z","abstract_excerpt":"Nuclear shape transition has been actively studied in the past decade. In particular, the understanding of this phenomenon from a microscopic point of view is of great importance. Because of this reason, many works have been employed to investigate shape phase transition in nuclei within the relativistic and non-relativistic mean field models by examining potential energy curves (PECs). In this paper, by using layered feed-forward neural networks (LFNNs), we have constructed consistent empirical physical formulas (EPFs) for the PECs of 38-66Ti calculated in Hartree-Fock-Bogoliubov (HFB) method"},"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":"1212.2007","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"nucl-th","submitted_at":"2012-12-10T09:41:43Z","cross_cats_sorted":[],"title_canon_sha256":"d6a106f82d00bf00093011047eb2c7699b00634fbc8cbc76d40c868cbfc6e89b","abstract_canon_sha256":"395a8db4edd854748f718657a92e5e467a4b0f4bd9abc30252020cbff77a87c9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:05:44.650037Z","signature_b64":"27ci9bUFFPxWDm6hwNLuFsnr0HYwnaycAAYzSUvcD2vCE3QjcuYtknLuGBZLINPuOpNKvSVTTFSdBW/D81VoAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"744748a58b66e8fbcf5fb076a6608570eef7f542b2dd21aafb1590db4ad24efc","last_reissued_at":"2026-05-18T03:05:44.649401Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:05:44.649401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Empirical physical formula for potential energy curves of 38-66Ti isotopes by using neural networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"nucl-th","authors_text":"N. Yildiz, S. Akkoyun, S. O. Kara, T. Bayram","submitted_at":"2012-12-10T09:41:43Z","abstract_excerpt":"Nuclear shape transition has been actively studied in the past decade. In particular, the understanding of this phenomenon from a microscopic point of view is of great importance. Because of this reason, many works have been employed to investigate shape phase transition in nuclei within the relativistic and non-relativistic mean field models by examining potential energy curves (PECs). In this paper, by using layered feed-forward neural networks (LFNNs), we have constructed consistent empirical physical formulas (EPFs) for the PECs of 38-66Ti calculated in Hartree-Fock-Bogoliubov (HFB) method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1212.2007","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":""},"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":"1212.2007","created_at":"2026-05-18T03:05:44.649511+00:00"},{"alias_kind":"arxiv_version","alias_value":"1212.2007v1","created_at":"2026-05-18T03:05:44.649511+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1212.2007","created_at":"2026-05-18T03:05:44.649511+00:00"},{"alias_kind":"pith_short_12","alias_value":"ORDURJMLM3UP","created_at":"2026-05-18T12:27:16.716162+00:00"},{"alias_kind":"pith_short_16","alias_value":"ORDURJMLM3UPXT27","created_at":"2026-05-18T12:27:16.716162+00:00"},{"alias_kind":"pith_short_8","alias_value":"ORDURJML","created_at":"2026-05-18T12:27:16.716162+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/ORDURJMLM3UPXT27WB3KMYEFOD","json":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD.json","graph_json":"https://pith.science/api/pith-number/ORDURJMLM3UPXT27WB3KMYEFOD/graph.json","events_json":"https://pith.science/api/pith-number/ORDURJMLM3UPXT27WB3KMYEFOD/events.json","paper":"https://pith.science/paper/ORDURJML"},"agent_actions":{"view_html":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD","download_json":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD.json","view_paper":"https://pith.science/paper/ORDURJML","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1212.2007&json=true","fetch_graph":"https://pith.science/api/pith-number/ORDURJMLM3UPXT27WB3KMYEFOD/graph.json","fetch_events":"https://pith.science/api/pith-number/ORDURJMLM3UPXT27WB3KMYEFOD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD/action/storage_attestation","attest_author":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD/action/author_attestation","sign_citation":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD/action/citation_signature","submit_replication":"https://pith.science/pith/ORDURJMLM3UPXT27WB3KMYEFOD/action/replication_record"}},"created_at":"2026-05-18T03:05:44.649511+00:00","updated_at":"2026-05-18T03:05:44.649511+00:00"}