{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:FJDIH4KELTKO375OOALCYX2NNT","short_pith_number":"pith:FJDIH4KE","schema_version":"1.0","canonical_sha256":"2a4683f1445cd4edffae70162c5f4d6cd01734f59d883a25a33958ee907b4be3","source":{"kind":"arxiv","id":"1701.01897","version":1},"attestation_state":"computed","paper":{"title":"Rate Constants for Fine-Structure Excitations in O-H Collisions with Error Bars Obtained by Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"astro-ph.GA","authors_text":"Daniel Vieira, Roman Krems","submitted_at":"2017-01-08T00:24:37Z","abstract_excerpt":"We present an approach using a combination of coupled channel scattering calculations with a machine- learning technique based on Gaussian Process regression to determine the sensitivity of the rate constants for non-adiabatic transitions in inelastic atomic collisions to variations of the underlying adiabatic interaction potentials. Using this approach, we improve the previous computations of the rate constants for the fine-structure transitions in collisions of O(3Pj) with atomic H. We compute the error bars of the rate constants corresponding to 20 % variations of the ab initio potentials a"},"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":"1701.01897","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.GA","submitted_at":"2017-01-08T00:24:37Z","cross_cats_sorted":["physics.chem-ph"],"title_canon_sha256":"512b690898580d2794e8f75d737523c59a41bbf6ac0d9737f30dd29d16b01f3b","abstract_canon_sha256":"6f18692786eb8df46ab8d4954793f395cff73cc924810cda2210ef52805c3f0b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:51:11.970426Z","signature_b64":"ng1uvSPK0ej3AScIztk7xd6f4ZppYoaCdO/HTsblV465+JwcwgVaf0RTV6sLx9uRBypMICzxh9zDoEyTh5yLDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a4683f1445cd4edffae70162c5f4d6cd01734f59d883a25a33958ee907b4be3","last_reissued_at":"2026-05-18T00:51:11.969709Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:51:11.969709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rate Constants for Fine-Structure Excitations in O-H Collisions with Error Bars Obtained by Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.chem-ph"],"primary_cat":"astro-ph.GA","authors_text":"Daniel Vieira, Roman Krems","submitted_at":"2017-01-08T00:24:37Z","abstract_excerpt":"We present an approach using a combination of coupled channel scattering calculations with a machine- learning technique based on Gaussian Process regression to determine the sensitivity of the rate constants for non-adiabatic transitions in inelastic atomic collisions to variations of the underlying adiabatic interaction potentials. Using this approach, we improve the previous computations of the rate constants for the fine-structure transitions in collisions of O(3Pj) with atomic H. We compute the error bars of the rate constants corresponding to 20 % variations of the ab initio potentials a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1701.01897","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":"1701.01897","created_at":"2026-05-18T00:51:11.969842+00:00"},{"alias_kind":"arxiv_version","alias_value":"1701.01897v1","created_at":"2026-05-18T00:51:11.969842+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1701.01897","created_at":"2026-05-18T00:51:11.969842+00:00"},{"alias_kind":"pith_short_12","alias_value":"FJDIH4KELTKO","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_16","alias_value":"FJDIH4KELTKO375O","created_at":"2026-05-18T12:31:15.632608+00:00"},{"alias_kind":"pith_short_8","alias_value":"FJDIH4KE","created_at":"2026-05-18T12:31:15.632608+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/FJDIH4KELTKO375OOALCYX2NNT","json":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT.json","graph_json":"https://pith.science/api/pith-number/FJDIH4KELTKO375OOALCYX2NNT/graph.json","events_json":"https://pith.science/api/pith-number/FJDIH4KELTKO375OOALCYX2NNT/events.json","paper":"https://pith.science/paper/FJDIH4KE"},"agent_actions":{"view_html":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT","download_json":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT.json","view_paper":"https://pith.science/paper/FJDIH4KE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1701.01897&json=true","fetch_graph":"https://pith.science/api/pith-number/FJDIH4KELTKO375OOALCYX2NNT/graph.json","fetch_events":"https://pith.science/api/pith-number/FJDIH4KELTKO375OOALCYX2NNT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT/action/storage_attestation","attest_author":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT/action/author_attestation","sign_citation":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT/action/citation_signature","submit_replication":"https://pith.science/pith/FJDIH4KELTKO375OOALCYX2NNT/action/replication_record"}},"created_at":"2026-05-18T00:51:11.969842+00:00","updated_at":"2026-05-18T00:51:11.969842+00:00"}