{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:1995:SF2A2YBYFDVC7KJPZE4FUFKJNC","short_pith_number":"pith:SF2A2YBY","schema_version":"1.0","canonical_sha256":"91740d603828ea2fa92fc9385a154968b197c92d022352a42e84e5ee04ca85f8","source":{"kind":"arxiv","id":"hep-ph/9502367","version":1},"attestation_state":"computed","paper":{"title":"JET ANALYSIS BY NEURAL NETWORKS IN HIGH ENERGY HADRON-HADRON COLLISIONS","license":"","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"G. Nardulli, G. Pasquariello, P. De Felice","submitted_at":"1995-02-22T16:21:04Z","abstract_excerpt":"We study the possibility to employ neural networks to simulate jet clustering procedures in high energy hadron-hadron collisions. We concentrate our analysis on the Fermilab Tevatron energy and on the $k_\\bot$ algorithm. We consider both supervised multilayer feed-forward network trained by the backpropagation algorithm and unsupervised learning, where the neural network autonomously organizes the events in clusters."},"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":"hep-ph/9502367","kind":"arxiv","version":1},"metadata":{"license":"","primary_cat":"hep-ph","submitted_at":"1995-02-22T16:21:04Z","cross_cats_sorted":[],"title_canon_sha256":"d4624470d57fc83f71c303c3996aa55cc6e300fde4cc136de05d401b5ae876e8","abstract_canon_sha256":"8990d2d79137f964c0c46749f05440ad2b4467b0cb1475a73a12bf38a7efcfe0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:06:33.341585Z","signature_b64":"GR6pvstAO9BOcCSXfZcaXd1BXnubJO41UPgLo/Umys2jKY29rpr1mB+YZftrdmGMgptOhZRNfcL/RaA7CIk+Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"91740d603828ea2fa92fc9385a154968b197c92d022352a42e84e5ee04ca85f8","last_reissued_at":"2026-05-18T01:06:33.341067Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:06:33.341067Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"JET ANALYSIS BY NEURAL NETWORKS IN HIGH ENERGY HADRON-HADRON COLLISIONS","license":"","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"G. Nardulli, G. Pasquariello, P. De Felice","submitted_at":"1995-02-22T16:21:04Z","abstract_excerpt":"We study the possibility to employ neural networks to simulate jet clustering procedures in high energy hadron-hadron collisions. We concentrate our analysis on the Fermilab Tevatron energy and on the $k_\\bot$ algorithm. We consider both supervised multilayer feed-forward network trained by the backpropagation algorithm and unsupervised learning, where the neural network autonomously organizes the events in clusters."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"hep-ph/9502367","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":"hep-ph/9502367","created_at":"2026-05-18T01:06:33.341154+00:00"},{"alias_kind":"arxiv_version","alias_value":"hep-ph/9502367v1","created_at":"2026-05-18T01:06:33.341154+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.hep-ph/9502367","created_at":"2026-05-18T01:06:33.341154+00:00"},{"alias_kind":"pith_short_12","alias_value":"SF2A2YBYFDVC","created_at":"2026-05-18T12:25:47.700082+00:00"},{"alias_kind":"pith_short_16","alias_value":"SF2A2YBYFDVC7KJP","created_at":"2026-05-18T12:25:47.700082+00:00"},{"alias_kind":"pith_short_8","alias_value":"SF2A2YBY","created_at":"2026-05-18T12:25:47.700082+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/SF2A2YBYFDVC7KJPZE4FUFKJNC","json":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC.json","graph_json":"https://pith.science/api/pith-number/SF2A2YBYFDVC7KJPZE4FUFKJNC/graph.json","events_json":"https://pith.science/api/pith-number/SF2A2YBYFDVC7KJPZE4FUFKJNC/events.json","paper":"https://pith.science/paper/SF2A2YBY"},"agent_actions":{"view_html":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC","download_json":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC.json","view_paper":"https://pith.science/paper/SF2A2YBY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=hep-ph/9502367&json=true","fetch_graph":"https://pith.science/api/pith-number/SF2A2YBYFDVC7KJPZE4FUFKJNC/graph.json","fetch_events":"https://pith.science/api/pith-number/SF2A2YBYFDVC7KJPZE4FUFKJNC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC/action/storage_attestation","attest_author":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC/action/author_attestation","sign_citation":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC/action/citation_signature","submit_replication":"https://pith.science/pith/SF2A2YBYFDVC7KJPZE4FUFKJNC/action/replication_record"}},"created_at":"2026-05-18T01:06:33.341154+00:00","updated_at":"2026-05-18T01:06:33.341154+00:00"}