{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6NB76ZA4VR7OR7BGIUTCATS753","short_pith_number":"pith:6NB76ZA4","schema_version":"1.0","canonical_sha256":"f343ff641cac7ee8fc264526204e5feeca958e51a0d20741538aabe89b6279c9","source":{"kind":"arxiv","id":"2607.02703","version":1},"attestation_state":"computed","paper":{"title":"LLMoxie: Exploring Agentic AI for Scientific Software Development","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.DC","cs.MA"],"primary_cat":"cs.SE","authors_text":"Anant Mittal, Andrew J. Connolly, Anshul Tambay, Carlos Garcia Jurado Suarez, Cordero Core, David A. C. Beck, Landung Setiawan, Vani Mandava","submitted_at":"2026-07-02T18:46:27Z","abstract_excerpt":"In this paper, we describe LLMoxie, an institutional AI platform whose three-tiered architecture supports multi-cloud and on-premise inference, a LiteLLM/MLflow control plane for authentication, budgeting, PII masking, and observability, and an application augmentation layer for AI coding agents. Layered on top, an open-source RSE-Plugins ecosystem encodes accumulated RSE knowledge as a Plugin-Agent-Skill hierarchy spanning scientific Python practice, domain-specific knowledge, a six-phase research-and-implement workflow, and project lifecycle management. Scientific software is judged less by "},"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":"2607.02703","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2026-07-02T18:46:27Z","cross_cats_sorted":["cs.AI","cs.DC","cs.MA"],"title_canon_sha256":"ececb6bf0565b69d3103b20039fe173a74525c2a6f15a558f3a6623758376535","abstract_canon_sha256":"840c11adfb5766c94565b5d85b4eb9ba7187e5090fc35e595b12d88577c563be"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T00:16:09.398784Z","signature_b64":"QUnsowroZqzhMFpeR9P5KT9Tv0pj/wVKFrIyXnjgLgq2/cs3KrtWKGMN6aR6RvVDJWWgb6FKz29tXeBi8DY9Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f343ff641cac7ee8fc264526204e5feeca958e51a0d20741538aabe89b6279c9","last_reissued_at":"2026-07-07T00:16:09.397656Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T00:16:09.397656Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLMoxie: Exploring Agentic AI for Scientific Software Development","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.DC","cs.MA"],"primary_cat":"cs.SE","authors_text":"Anant Mittal, Andrew J. Connolly, Anshul Tambay, Carlos Garcia Jurado Suarez, Cordero Core, David A. C. Beck, Landung Setiawan, Vani Mandava","submitted_at":"2026-07-02T18:46:27Z","abstract_excerpt":"In this paper, we describe LLMoxie, an institutional AI platform whose three-tiered architecture supports multi-cloud and on-premise inference, a LiteLLM/MLflow control plane for authentication, budgeting, PII masking, and observability, and an application augmentation layer for AI coding agents. Layered on top, an open-source RSE-Plugins ecosystem encodes accumulated RSE knowledge as a Plugin-Agent-Skill hierarchy spanning scientific Python practice, domain-specific knowledge, a six-phase research-and-implement workflow, and project lifecycle management. Scientific software is judged less by "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.02703","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.02703/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":"2607.02703","created_at":"2026-07-07T00:16:09.397832+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.02703v1","created_at":"2026-07-07T00:16:09.397832+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.02703","created_at":"2026-07-07T00:16:09.397832+00:00"},{"alias_kind":"pith_short_12","alias_value":"6NB76ZA4VR7O","created_at":"2026-07-07T00:16:09.397832+00:00"},{"alias_kind":"pith_short_16","alias_value":"6NB76ZA4VR7OR7BG","created_at":"2026-07-07T00:16:09.397832+00:00"},{"alias_kind":"pith_short_8","alias_value":"6NB76ZA4","created_at":"2026-07-07T00:16:09.397832+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/6NB76ZA4VR7OR7BGIUTCATS753","json":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753.json","graph_json":"https://pith.science/api/pith-number/6NB76ZA4VR7OR7BGIUTCATS753/graph.json","events_json":"https://pith.science/api/pith-number/6NB76ZA4VR7OR7BGIUTCATS753/events.json","paper":"https://pith.science/paper/6NB76ZA4"},"agent_actions":{"view_html":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753","download_json":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753.json","view_paper":"https://pith.science/paper/6NB76ZA4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.02703&json=true","fetch_graph":"https://pith.science/api/pith-number/6NB76ZA4VR7OR7BGIUTCATS753/graph.json","fetch_events":"https://pith.science/api/pith-number/6NB76ZA4VR7OR7BGIUTCATS753/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753/action/storage_attestation","attest_author":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753/action/author_attestation","sign_citation":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753/action/citation_signature","submit_replication":"https://pith.science/pith/6NB76ZA4VR7OR7BGIUTCATS753/action/replication_record"}},"created_at":"2026-07-07T00:16:09.397832+00:00","updated_at":"2026-07-07T00:16:09.397832+00:00"}