{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MNBJIQ3UEFLR6KY6V5F7AP6L7C","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":"dbaadba4bdd4533ce9005f5275e99fe236bdccb5d8bed7cdf33eca51e1817a0c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-17T05:24:32Z","title_canon_sha256":"4ca5703d974699c1704fa6f9f248600111d226eabfbf9dc496d2393fb04ef0b7"},"schema_version":"1.0","source":{"id":"2606.18698","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.18698","created_at":"2026-06-19T16:11:44Z"},{"alias_kind":"arxiv_version","alias_value":"2606.18698v1","created_at":"2026-06-19T16:11:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18698","created_at":"2026-06-19T16:11:44Z"},{"alias_kind":"pith_short_12","alias_value":"MNBJIQ3UEFLR","created_at":"2026-06-19T16:11:44Z"},{"alias_kind":"pith_short_16","alias_value":"MNBJIQ3UEFLR6KY6","created_at":"2026-06-19T16:11:44Z"},{"alias_kind":"pith_short_8","alias_value":"MNBJIQ3U","created_at":"2026-06-19T16:11:44Z"}],"graph_snapshots":[{"event_id":"sha256:5e89d2db2cde5cde8093c7f7a449d6106ec7d88a57780628a44a16dcd0ceaa12","target":"graph","created_at":"2026-06-19T16:11:44Z","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/2606.18698/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The energy-based method remains a comparatively underexamined approach for surface classification in mobile robotics, despite promising results in constrained environments. This study evaluated the viability of using energy-derived features as either a standalone classification modality or as supplementary input to inertial data. A comprehensive evaluation was conducted across three publicly available datasets, comparing the performance of modern deep learning architectures including recurrent neural networks, convolutional neural networks, encoder-only transformers, and Mamba state-space mode","authors_text":"Alexander Belyaev, Oleg Kushnarev","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-17T05:24:32Z","title":"Leveraging Energy Features for Surface Classification with Deep Learning: A Comparative Analysis Across Three Independent Datasets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18698","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":"sha256:7fa263bb969e30a7a3fd433a7e36405042b363ec5ccb28029e43f3993f0b978a","target":"record","created_at":"2026-06-19T16:11:44Z","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":"dbaadba4bdd4533ce9005f5275e99fe236bdccb5d8bed7cdf33eca51e1817a0c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-17T05:24:32Z","title_canon_sha256":"4ca5703d974699c1704fa6f9f248600111d226eabfbf9dc496d2393fb04ef0b7"},"schema_version":"1.0","source":{"id":"2606.18698","kind":"arxiv","version":1}},"canonical_sha256":"634294437421571f2b1eaf4bf03fcbf88151abe0c907e090f26cbbe3360482aa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"634294437421571f2b1eaf4bf03fcbf88151abe0c907e090f26cbbe3360482aa","first_computed_at":"2026-06-19T16:11:44.802617Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:11:44.802617Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SEPT/uu6mQJhhFnASgqt7CMyFOLJXxVfWlBisbukKw4HlRhB2SEFy2N0PUm/gZS/1WFWaNkOpA0TmYx6o33FAA==","signature_status":"signed_v1","signed_at":"2026-06-19T16:11:44.803024Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.18698","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7fa263bb969e30a7a3fd433a7e36405042b363ec5ccb28029e43f3993f0b978a","sha256:5e89d2db2cde5cde8093c7f7a449d6106ec7d88a57780628a44a16dcd0ceaa12"],"state_sha256":"1e63d5f733b2d9b75a275d7f643a0a701d13b7df1458269e969a9b336c360587"}