{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XBYXYYOUOBIO6S2PU5WBLLTIPD","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":"080d0b1b80aebd356b997f8b32fd059fc899d785cc72be5ea0907b198fcd3a33","cross_cats_sorted":["cs.CV","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-26T11:33:52Z","title_canon_sha256":"ed9d77a506a5cbfd8265b2a6df4e54ad24899c17b6e31f68d7d20e78c747d731"},"schema_version":"1.0","source":{"id":"2003.11842","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.11842","created_at":"2026-07-05T00:50:48Z"},{"alias_kind":"arxiv_version","alias_value":"2003.11842v1","created_at":"2026-07-05T00:50:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.11842","created_at":"2026-07-05T00:50:48Z"},{"alias_kind":"pith_short_12","alias_value":"XBYXYYOUOBIO","created_at":"2026-07-05T00:50:48Z"},{"alias_kind":"pith_short_16","alias_value":"XBYXYYOUOBIO6S2P","created_at":"2026-07-05T00:50:48Z"},{"alias_kind":"pith_short_8","alias_value":"XBYXYYOU","created_at":"2026-07-05T00:50:48Z"}],"graph_snapshots":[{"event_id":"sha256:6e82cd7c85d74360d60e105cf44813c52553cef192beb5c5c0d6c5ecb1273d11","target":"graph","created_at":"2026-07-05T00:50:48Z","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/2003.11842/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art approaches. The specific task we consider is identifying whether samples contain chlorinated solvents or not, based on their Raman spectra. We also examine robustness to classification of outlier samples that are not represented in the training set (negative outliers). A novel application of a locally-connected neural network (NN) for the binary classification of spectroscopy data is proposed and demonstrated to yield improved accuracy o","authors_text":"Frank G. Glavin, James Houston, Michael G. Madden","cross_cats":["cs.CV","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-26T11:33:52Z","title":"Robust Classification of High-Dimensional Spectroscopy Data Using Deep Learning and Data Synthesis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.11842","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:c87c486afca2c5b7de01b1159ac78f37bbcc394002de36c61f32a528d375ff36","target":"record","created_at":"2026-07-05T00:50:48Z","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":"080d0b1b80aebd356b997f8b32fd059fc899d785cc72be5ea0907b198fcd3a33","cross_cats_sorted":["cs.CV","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-03-26T11:33:52Z","title_canon_sha256":"ed9d77a506a5cbfd8265b2a6df4e54ad24899c17b6e31f68d7d20e78c747d731"},"schema_version":"1.0","source":{"id":"2003.11842","kind":"arxiv","version":1}},"canonical_sha256":"b8717c61d47050ef4b4fa76c15ae6878ca98903d011b0b86a70fd233a3bd8548","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b8717c61d47050ef4b4fa76c15ae6878ca98903d011b0b86a70fd233a3bd8548","first_computed_at":"2026-07-05T00:50:48.066724Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:50:48.066724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5wmvYUg3geymI/AmfzEZuGDpkf0ExggO0X2wiW/ew/DWhzkdrAQ9KFuz+iEojLdG+Ty6lltmlaLRVgfvJCbAAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:50:48.067171Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.11842","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c87c486afca2c5b7de01b1159ac78f37bbcc394002de36c61f32a528d375ff36","sha256:6e82cd7c85d74360d60e105cf44813c52553cef192beb5c5c0d6c5ecb1273d11"],"state_sha256":"6fb415ddeddf862302459c1c502eee4bf14eda4abc908d4b30c1e17442885bbb"}