{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:3ZM46Q7RSX4U52HLE56AWMHUGN","short_pith_number":"pith:3ZM46Q7R","schema_version":"1.0","canonical_sha256":"de59cf43f195f94ee8eb277c0b30f43356a8cb309e3ae05facf320c5ff5171d7","source":{"kind":"arxiv","id":"2607.00956","version":1},"attestation_state":"computed","paper":{"title":"Aionoscope: Debugging Latent-State Accessibility in Time-Series Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alexander Chemeris, Ming Jin, Randall Balestriero","submitted_at":"2026-07-01T13:54:20Z","abstract_excerpt":"Time-series models are often evaluated by what they can forecast or classify, but those scores do not show whether their representations preserve the process state a user may want to inspect: event timing, phase, amplitude, frequency, or regime variables. We introduce Aionoscope, a generator-based diagnostic tool for debugging latent-state accessibility in frozen time-series representations. Aionoscope separates process generation from observation rendering, producing seeded synthetic streams with exact categorical and dense labels across mixture complexity and nuisance variation.\n  We instant"},"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":"2607.00956","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-01T13:54:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"76d6d15909ca12c0116f8a8357b4b0a0732e85127838c085c9fa4332feed8bc4","abstract_canon_sha256":"ff37403d6a80bfc64cefab2e648a2dc1ed363e382b3cc97cf4e31ae94d46ac68"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T01:18:24.466658Z","signature_b64":"slkAgz998/xAKdXtwDWUUn2vqvMYHDWrEZjHMHpqQbdBmvjOIoLnyMYJvUFBy9QjK3yR849OjlIshlYTS6pVCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"de59cf43f195f94ee8eb277c0b30f43356a8cb309e3ae05facf320c5ff5171d7","last_reissued_at":"2026-07-02T01:18:24.466273Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T01:18:24.466273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Aionoscope: Debugging Latent-State Accessibility in Time-Series Representations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alexander Chemeris, Ming Jin, Randall Balestriero","submitted_at":"2026-07-01T13:54:20Z","abstract_excerpt":"Time-series models are often evaluated by what they can forecast or classify, but those scores do not show whether their representations preserve the process state a user may want to inspect: event timing, phase, amplitude, frequency, or regime variables. We introduce Aionoscope, a generator-based diagnostic tool for debugging latent-state accessibility in frozen time-series representations. Aionoscope separates process generation from observation rendering, producing seeded synthetic streams with exact categorical and dense labels across mixture complexity and nuisance variation.\n  We instant"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00956","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/2607.00956/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":"2607.00956","created_at":"2026-07-02T01:18:24.466344+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.00956v1","created_at":"2026-07-02T01:18:24.466344+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00956","created_at":"2026-07-02T01:18:24.466344+00:00"},{"alias_kind":"pith_short_12","alias_value":"3ZM46Q7RSX4U","created_at":"2026-07-02T01:18:24.466344+00:00"},{"alias_kind":"pith_short_16","alias_value":"3ZM46Q7RSX4U52HL","created_at":"2026-07-02T01:18:24.466344+00:00"},{"alias_kind":"pith_short_8","alias_value":"3ZM46Q7R","created_at":"2026-07-02T01:18:24.466344+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/3ZM46Q7RSX4U52HLE56AWMHUGN","json":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN.json","graph_json":"https://pith.science/api/pith-number/3ZM46Q7RSX4U52HLE56AWMHUGN/graph.json","events_json":"https://pith.science/api/pith-number/3ZM46Q7RSX4U52HLE56AWMHUGN/events.json","paper":"https://pith.science/paper/3ZM46Q7R"},"agent_actions":{"view_html":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN","download_json":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN.json","view_paper":"https://pith.science/paper/3ZM46Q7R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.00956&json=true","fetch_graph":"https://pith.science/api/pith-number/3ZM46Q7RSX4U52HLE56AWMHUGN/graph.json","fetch_events":"https://pith.science/api/pith-number/3ZM46Q7RSX4U52HLE56AWMHUGN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN/action/storage_attestation","attest_author":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN/action/author_attestation","sign_citation":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN/action/citation_signature","submit_replication":"https://pith.science/pith/3ZM46Q7RSX4U52HLE56AWMHUGN/action/replication_record"}},"created_at":"2026-07-02T01:18:24.466344+00:00","updated_at":"2026-07-02T01:18:24.466344+00:00"}