{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:VJ6NWNB6OBIZEC7FRB2ZLLENCU","short_pith_number":"pith:VJ6NWNB6","canonical_record":{"source":{"id":"2607.18308","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-17T13:34:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5f8d0e62af1e9db53626689b14b363d256d20e38b5ab375003ef09ebacbf780e","abstract_canon_sha256":"5d6c62167c20e4882e53c8fb530cb11b35fd7cc96dd21ab371afe73e60174e86"},"schema_version":"1.0"},"canonical_sha256":"aa7cdb343e7051920be5887595ac8d15103c6580e2ce6e758494580f365f6cff","source":{"kind":"arxiv","id":"2607.18308","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18308","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18308v1","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18308","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_12","alias_value":"VJ6NWNB6OBIZ","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_16","alias_value":"VJ6NWNB6OBIZEC7F","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_8","alias_value":"VJ6NWNB6","created_at":"2026-07-22T00:22:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:VJ6NWNB6OBIZEC7FRB2ZLLENCU","target":"record","payload":{"canonical_record":{"source":{"id":"2607.18308","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-17T13:34:26Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5f8d0e62af1e9db53626689b14b363d256d20e38b5ab375003ef09ebacbf780e","abstract_canon_sha256":"5d6c62167c20e4882e53c8fb530cb11b35fd7cc96dd21ab371afe73e60174e86"},"schema_version":"1.0"},"canonical_sha256":"aa7cdb343e7051920be5887595ac8d15103c6580e2ce6e758494580f365f6cff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-22T00:22:41.029622Z","signature_b64":"Yk3YflQDZtT60ujEYzPz/ega9v5rq022JHSNPtWIXpYLet6j6ed0MI8ifBGhuGvf8o1EeMH75s98SJ+fT3OFDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa7cdb343e7051920be5887595ac8d15103c6580e2ce6e758494580f365f6cff","last_reissued_at":"2026-07-22T00:22:41.028906Z","signature_status":"signed_v1","first_computed_at":"2026-07-22T00:22:41.028906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.18308","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-22T00:22:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DaeGlLiqW8vV6bF4E4BIIpAPzmUcgdPpGvgzAereLZNyukthQnLbl00nFupmn7bS2dnuBNwq3xNRJvuIvt5SCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T08:16:02.450842Z"},"content_sha256":"a075efb8a28bd9e5b40c59b1c0ddd081858c3b8f8db1816f036d3a7767d374bf","schema_version":"1.0","event_id":"sha256:a075efb8a28bd9e5b40c59b1c0ddd081858c3b8f8db1816f036d3a7767d374bf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:VJ6NWNB6OBIZEC7FRB2ZLLENCU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Agentic Calibration of Grey-Box Simulation Models: An LLM-Driven Alternative","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"David G\\'omez-Guill\\'en, Jes\\'us Cerquides, Josep Lluis Arcos, Mireia Diaz","submitted_at":"2026-07-17T13:34:26Z","abstract_excerpt":"Calibration of grey-box simulation models is a constrained optimization problem in which model evaluations are expensive, the parameter space can be high-dimensional, and the search must respect plausibility constraints. Although the simulation code is fully available to the analyst, the joint effect of multiple parameters remains difficult to predict analytically. Classical optimizers such as Nelder--Mead (NM) are simple to deploy but sample-inefficient, particularly under constraints. Modern Bayesian Optimization methods achieve competitive solutions with far fewer evaluations but require no"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18308","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/2607.18308/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-22T00:22:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BIhEEjYEhrwPDd8QTjviFLSG3LWHcnk34XEyV90GOx9OO11b+8qEQMoInQABL8T7DZJRoKFIJY02r5u8Y7JICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T08:16:02.451804Z"},"content_sha256":"c779faec6b6b8068e8116e0ad52abfbf726017e61ff555f1b5846e0291eb3707","schema_version":"1.0","event_id":"sha256:c779faec6b6b8068e8116e0ad52abfbf726017e61ff555f1b5846e0291eb3707"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/bundle.json","state_url":"https://pith.science/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T08:16:02Z","links":{"resolver":"https://pith.science/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU","bundle":"https://pith.science/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/bundle.json","state":"https://pith.science/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VJ6NWNB6OBIZEC7FRB2ZLLENCU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:VJ6NWNB6OBIZEC7FRB2ZLLENCU","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"5d6c62167c20e4882e53c8fb530cb11b35fd7cc96dd21ab371afe73e60174e86","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-17T13:34:26Z","title_canon_sha256":"5f8d0e62af1e9db53626689b14b363d256d20e38b5ab375003ef09ebacbf780e"},"schema_version":"1.0","source":{"id":"2607.18308","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18308","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18308v1","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18308","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_12","alias_value":"VJ6NWNB6OBIZ","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_16","alias_value":"VJ6NWNB6OBIZEC7F","created_at":"2026-07-22T00:22:41Z"},{"alias_kind":"pith_short_8","alias_value":"VJ6NWNB6","created_at":"2026-07-22T00:22:41Z"}],"graph_snapshots":[{"event_id":"sha256:c779faec6b6b8068e8116e0ad52abfbf726017e61ff555f1b5846e0291eb3707","target":"graph","created_at":"2026-07-22T00:22:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.18308/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Calibration of grey-box simulation models is a constrained optimization problem in which model evaluations are expensive, the parameter space can be high-dimensional, and the search must respect plausibility constraints. Although the simulation code is fully available to the analyst, the joint effect of multiple parameters remains difficult to predict analytically. Classical optimizers such as Nelder--Mead (NM) are simple to deploy but sample-inefficient, particularly under constraints. Modern Bayesian Optimization methods achieve competitive solutions with far fewer evaluations but require no","authors_text":"David G\\'omez-Guill\\'en, Jes\\'us Cerquides, Josep Lluis Arcos, Mireia Diaz","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-17T13:34:26Z","title":"Agentic Calibration of Grey-Box Simulation Models: An LLM-Driven Alternative"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18308","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:a075efb8a28bd9e5b40c59b1c0ddd081858c3b8f8db1816f036d3a7767d374bf","target":"record","created_at":"2026-07-22T00:22:41Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"5d6c62167c20e4882e53c8fb530cb11b35fd7cc96dd21ab371afe73e60174e86","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-17T13:34:26Z","title_canon_sha256":"5f8d0e62af1e9db53626689b14b363d256d20e38b5ab375003ef09ebacbf780e"},"schema_version":"1.0","source":{"id":"2607.18308","kind":"arxiv","version":1}},"canonical_sha256":"aa7cdb343e7051920be5887595ac8d15103c6580e2ce6e758494580f365f6cff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa7cdb343e7051920be5887595ac8d15103c6580e2ce6e758494580f365f6cff","first_computed_at":"2026-07-22T00:22:41.028906Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-22T00:22:41.028906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Yk3YflQDZtT60ujEYzPz/ega9v5rq022JHSNPtWIXpYLet6j6ed0MI8ifBGhuGvf8o1EeMH75s98SJ+fT3OFDg==","signature_status":"signed_v1","signed_at":"2026-07-22T00:22:41.029622Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.18308","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a075efb8a28bd9e5b40c59b1c0ddd081858c3b8f8db1816f036d3a7767d374bf","sha256:c779faec6b6b8068e8116e0ad52abfbf726017e61ff555f1b5846e0291eb3707"],"state_sha256":"5254413386f3f538c2e4e7ad28f6ac41beb11ea812d0e124c435b542861f123a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DV5lbOEbxYsGsWTZ2dx626lOxjHvc9wmWd2jZzn8/XuUi7POEX1/i8Y9WQijNxPuYnt159hTihvkCyIlYPrXCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T08:16:02.458147Z","bundle_sha256":"b45254740dec22011879f3c2d0e16a347d671764ca14d13f877322ed4dda2d58"}}