{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:E6PQDC3NIH3TW4UHHMKF3TILML","short_pith_number":"pith:E6PQDC3N","schema_version":"1.0","canonical_sha256":"279f018b6d41f73b72873b145dcd0b62c562a83e570d33f6ebb9e01b64d9fd08","source":{"kind":"arxiv","id":"2409.13529","version":2},"attestation_state":"computed","paper":{"title":"Duqtools: Dynamic uncertainty quantification for Tokamak reactor simulations modelling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.plasm-ph","authors_text":"Aaron Ho, Florian Koechl, Francis Casson, Jonathan Citrin, Stef Smeets, Victor Azizi","submitted_at":"2024-09-20T14:15:38Z","abstract_excerpt":"Large scale validation and uncertainty quantification are essential in the experimental design, control, and operations of fusion reactors. Reduced models and increasing computational power means that it is possible to run many simulations, yet setting up simulation runs remaining a time-consuming and error-prone process that involves many manual steps. duqtools is an open-source workflow tool written in Python for that addresses this bottleneck by automating the set up of new simulations. This enables uncertainty quantification and large scale validation of fusion energy modelling simulations"},"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":"2409.13529","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.plasm-ph","submitted_at":"2024-09-20T14:15:38Z","cross_cats_sorted":[],"title_canon_sha256":"78185e2440693672581e7f0944d15d98e34e51098f3cb73db0c50f47978fd384","abstract_canon_sha256":"62b225fc96c373bdc5b461e0b5e85c4af20db9963927780b715c9afbd98507df"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:02:52.281943Z","signature_b64":"5/8sLHS2R5QTi32qyQR/KiL30sY340N1x++z3xtbqOMuG3lDyFP/h8fPMenPBOjN1kRftbaH7SKncB0EVshsBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"279f018b6d41f73b72873b145dcd0b62c562a83e570d33f6ebb9e01b64d9fd08","last_reissued_at":"2026-07-05T10:02:52.281462Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:02:52.281462Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Duqtools: Dynamic uncertainty quantification for Tokamak reactor simulations modelling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"physics.plasm-ph","authors_text":"Aaron Ho, Florian Koechl, Francis Casson, Jonathan Citrin, Stef Smeets, Victor Azizi","submitted_at":"2024-09-20T14:15:38Z","abstract_excerpt":"Large scale validation and uncertainty quantification are essential in the experimental design, control, and operations of fusion reactors. Reduced models and increasing computational power means that it is possible to run many simulations, yet setting up simulation runs remaining a time-consuming and error-prone process that involves many manual steps. duqtools is an open-source workflow tool written in Python for that addresses this bottleneck by automating the set up of new simulations. This enables uncertainty quantification and large scale validation of fusion energy modelling simulations"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.13529","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.13529/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":"2409.13529","created_at":"2026-07-05T10:02:52.281523+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.13529v2","created_at":"2026-07-05T10:02:52.281523+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.13529","created_at":"2026-07-05T10:02:52.281523+00:00"},{"alias_kind":"pith_short_12","alias_value":"E6PQDC3NIH3T","created_at":"2026-07-05T10:02:52.281523+00:00"},{"alias_kind":"pith_short_16","alias_value":"E6PQDC3NIH3TW4UH","created_at":"2026-07-05T10:02:52.281523+00:00"},{"alias_kind":"pith_short_8","alias_value":"E6PQDC3N","created_at":"2026-07-05T10:02:52.281523+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/E6PQDC3NIH3TW4UHHMKF3TILML","json":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML.json","graph_json":"https://pith.science/api/pith-number/E6PQDC3NIH3TW4UHHMKF3TILML/graph.json","events_json":"https://pith.science/api/pith-number/E6PQDC3NIH3TW4UHHMKF3TILML/events.json","paper":"https://pith.science/paper/E6PQDC3N"},"agent_actions":{"view_html":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML","download_json":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML.json","view_paper":"https://pith.science/paper/E6PQDC3N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.13529&json=true","fetch_graph":"https://pith.science/api/pith-number/E6PQDC3NIH3TW4UHHMKF3TILML/graph.json","fetch_events":"https://pith.science/api/pith-number/E6PQDC3NIH3TW4UHHMKF3TILML/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML/action/storage_attestation","attest_author":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML/action/author_attestation","sign_citation":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML/action/citation_signature","submit_replication":"https://pith.science/pith/E6PQDC3NIH3TW4UHHMKF3TILML/action/replication_record"}},"created_at":"2026-07-05T10:02:52.281523+00:00","updated_at":"2026-07-05T10:02:52.281523+00:00"}