{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SAXPO7PKBK5GD34WG2A6DUNFKS","short_pith_number":"pith:SAXPO7PK","canonical_record":{"source":{"id":"2404.02180","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-02T09:15:32Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"711dc4636bd2be54e2581f0d0632cd5a8f3ab1e896a3ce08e546dedf01f5e9e5","abstract_canon_sha256":"61e1d4a690f036b9719818d349a830c5866239f13a1620b5f91a2c86e5f527d9"},"schema_version":"1.0"},"canonical_sha256":"902ef77dea0aba61ef963681e1d1a554a215711c8d89601e817237eecbf27c0c","source":{"kind":"arxiv","id":"2404.02180","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.02180","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"arxiv_version","alias_value":"2404.02180v4","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.02180","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_12","alias_value":"SAXPO7PKBK5G","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_16","alias_value":"SAXPO7PKBK5GD34W","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_8","alias_value":"SAXPO7PK","created_at":"2026-07-05T09:09:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SAXPO7PKBK5GD34WG2A6DUNFKS","target":"record","payload":{"canonical_record":{"source":{"id":"2404.02180","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-02T09:15:32Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"711dc4636bd2be54e2581f0d0632cd5a8f3ab1e896a3ce08e546dedf01f5e9e5","abstract_canon_sha256":"61e1d4a690f036b9719818d349a830c5866239f13a1620b5f91a2c86e5f527d9"},"schema_version":"1.0"},"canonical_sha256":"902ef77dea0aba61ef963681e1d1a554a215711c8d89601e817237eecbf27c0c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:09:58.248297Z","signature_b64":"97kNO9/Vb2DxrIHUHKV2tqFBZfjn6qjh+KfZKzmGyvoIad2PyHk+RHpQeGHm5Ae/l3EVOTSfJXXbVh/3WGk5Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"902ef77dea0aba61ef963681e1d1a554a215711c8d89601e817237eecbf27c0c","last_reissued_at":"2026-07-05T09:09:58.247736Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:09:58.247736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.02180","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:09:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ohBQt+4s2DxGCKHi0FE+3t+4ecCSG8vEsb680BHjIBAejlQifL5iH9x1vgTBUzeAGbbdT5TIYV/DvoiXLLsKAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:18:37.885150Z"},"content_sha256":"6d64fdf05819db986ae74a3917183bad0b81cea0f91a6ae7fc895edee9f55ca5","schema_version":"1.0","event_id":"sha256:6d64fdf05819db986ae74a3917183bad0b81cea0f91a6ae7fc895edee9f55ca5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SAXPO7PKBK5GD34WG2A6DUNFKS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Remote sensing framework for geological mapping via stacked autoencoders and clustering","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Ehsan Farahbakhsh, Joseph Awange, Rohitash Chandra, Sandeep Nagar","submitted_at":"2024-04-02T09:15:32Z","abstract_excerpt":"Supervised machine learning methods for geological mapping via remote sensing face limitations due to the scarcity of accurately labelled training data that can be addressed by unsupervised learning, such as dimensionality reduction and clustering. Dimensionality reduction methods have the potential to play a crucial role in improving the accuracy of geological maps. Although conventional dimensionality reduction methods may struggle with nonlinear data, unsupervised deep learning models such as autoencoders can model non-linear relationships. Stacked autoencoders feature multiple interconnect"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.02180","kind":"arxiv","version":4},"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/2404.02180/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":"2026-07-05T09:09:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GqjJRIyyI9A3BTKDmDr3rMFQllq8YUqFJSYKsxnVmSscQnblL5CtCGKIOkAfQaEtX+iyJ3gifGsEfN4olc56Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:18:37.885544Z"},"content_sha256":"53377f12a664ae151550f339c337454ab0259b0aaa118be8e26d63d0cdc1fc34","schema_version":"1.0","event_id":"sha256:53377f12a664ae151550f339c337454ab0259b0aaa118be8e26d63d0cdc1fc34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/bundle.json","state_url":"https://pith.science/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/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":"2026-07-06T16:18:37Z","links":{"resolver":"https://pith.science/pith/SAXPO7PKBK5GD34WG2A6DUNFKS","bundle":"https://pith.science/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/bundle.json","state":"https://pith.science/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SAXPO7PKBK5GD34WG2A6DUNFKS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SAXPO7PKBK5GD34WG2A6DUNFKS","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":"61e1d4a690f036b9719818d349a830c5866239f13a1620b5f91a2c86e5f527d9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-02T09:15:32Z","title_canon_sha256":"711dc4636bd2be54e2581f0d0632cd5a8f3ab1e896a3ce08e546dedf01f5e9e5"},"schema_version":"1.0","source":{"id":"2404.02180","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.02180","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"arxiv_version","alias_value":"2404.02180v4","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.02180","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_12","alias_value":"SAXPO7PKBK5G","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_16","alias_value":"SAXPO7PKBK5GD34W","created_at":"2026-07-05T09:09:58Z"},{"alias_kind":"pith_short_8","alias_value":"SAXPO7PK","created_at":"2026-07-05T09:09:58Z"}],"graph_snapshots":[{"event_id":"sha256:53377f12a664ae151550f339c337454ab0259b0aaa118be8e26d63d0cdc1fc34","target":"graph","created_at":"2026-07-05T09:09:58Z","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/2404.02180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Supervised machine learning methods for geological mapping via remote sensing face limitations due to the scarcity of accurately labelled training data that can be addressed by unsupervised learning, such as dimensionality reduction and clustering. Dimensionality reduction methods have the potential to play a crucial role in improving the accuracy of geological maps. Although conventional dimensionality reduction methods may struggle with nonlinear data, unsupervised deep learning models such as autoencoders can model non-linear relationships. Stacked autoencoders feature multiple interconnect","authors_text":"Ehsan Farahbakhsh, Joseph Awange, Rohitash Chandra, Sandeep Nagar","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-02T09:15:32Z","title":"Remote sensing framework for geological mapping via stacked autoencoders and clustering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.02180","kind":"arxiv","version":4},"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":"sha256:6d64fdf05819db986ae74a3917183bad0b81cea0f91a6ae7fc895edee9f55ca5","target":"record","created_at":"2026-07-05T09:09:58Z","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":"61e1d4a690f036b9719818d349a830c5866239f13a1620b5f91a2c86e5f527d9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-04-02T09:15:32Z","title_canon_sha256":"711dc4636bd2be54e2581f0d0632cd5a8f3ab1e896a3ce08e546dedf01f5e9e5"},"schema_version":"1.0","source":{"id":"2404.02180","kind":"arxiv","version":4}},"canonical_sha256":"902ef77dea0aba61ef963681e1d1a554a215711c8d89601e817237eecbf27c0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"902ef77dea0aba61ef963681e1d1a554a215711c8d89601e817237eecbf27c0c","first_computed_at":"2026-07-05T09:09:58.247736Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:09:58.247736Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"97kNO9/Vb2DxrIHUHKV2tqFBZfjn6qjh+KfZKzmGyvoIad2PyHk+RHpQeGHm5Ae/l3EVOTSfJXXbVh/3WGk5Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:09:58.248297Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.02180","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6d64fdf05819db986ae74a3917183bad0b81cea0f91a6ae7fc895edee9f55ca5","sha256:53377f12a664ae151550f339c337454ab0259b0aaa118be8e26d63d0cdc1fc34"],"state_sha256":"120bb27afbf2b0ddb04a675984c4985c845b54f53652d71a498cf0f02d9cd4b0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h4HAmfFRHaEE0G8h3cWZ9KGwIEC3yqqoajv7XHwjeouB8Qggrcip2V7rsLeCAXWcMz0uMPHHSf0Qp4Rew64fAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T16:18:37.887519Z","bundle_sha256":"89d4300262ea02acc4ceddfcad1ee68473799df967676046b7482c05e4213e2e"}}