{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:CJYRY3TRE6IHOSNPEQPXSAJBAQ","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":"1a2c05bd46709bc7c74d0c69f673b75160d53260c868858973a1408b363395a7","cross_cats_sorted":["math.AT","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-05T10:06:55Z","title_canon_sha256":"4d056cbbfa6d38cffa98a1c8650ecef0ef70fb102870ab4d7086f7e08aaabda3"},"schema_version":"1.0","source":{"id":"1904.02971","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.02971","created_at":"2026-05-17T23:49:19Z"},{"alias_kind":"arxiv_version","alias_value":"1904.02971v1","created_at":"2026-05-17T23:49:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02971","created_at":"2026-05-17T23:49:19Z"},{"alias_kind":"pith_short_12","alias_value":"CJYRY3TRE6IH","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"CJYRY3TRE6IHOSNP","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"CJYRY3TR","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:4c2c1aad1867aae6209ab99c461ee57e32d5783fb1ad2b8e37eab5db71917a41","target":"graph","created_at":"2026-05-17T23:49:19Z","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"},"paper":{"abstract_excerpt":"Machine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the data topology. When applying this to two case studies, accuracy exceeds alternative models with additional benefits such as reporting data subsets with high purity along with feature values. For 300 examples of 3 tree species, the accuracy reached 80% after 30 datapoints, which was improved to 90% after increased sampling to 400 datapoints. Using data from 100 examples of","authors_text":"Henri Riihim\\\"aki, Jakob Theorell, Jan Hillert, Ryan Ramanujam, Wojciech Chach\\'olski","cross_cats":["math.AT","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-05T10:06:55Z","title":"A topological data analysis based classification method for multiple measurements"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02971","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":"sha256:9fb6579b2eee1a13ec2b92e089db23034cb9feafa4d43d30fb57030af411fae0","target":"record","created_at":"2026-05-17T23:49:19Z","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":"1a2c05bd46709bc7c74d0c69f673b75160d53260c868858973a1408b363395a7","cross_cats_sorted":["math.AT","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-04-05T10:06:55Z","title_canon_sha256":"4d056cbbfa6d38cffa98a1c8650ecef0ef70fb102870ab4d7086f7e08aaabda3"},"schema_version":"1.0","source":{"id":"1904.02971","kind":"arxiv","version":1}},"canonical_sha256":"12711c6e7127907749af241f790121042fe945c83e1dee607044b822e7d8f12b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12711c6e7127907749af241f790121042fe945c83e1dee607044b822e7d8f12b","first_computed_at":"2026-05-17T23:49:19.050074Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:19.050074Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1R0hfnK+vtf/MKGQKegCf5mg+CE6GpOCV4A3HbAxgo7fFCWkKwNtDNYxIJMELPM1O9Q9sj57bkJI4sYxU5ngAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:19.050677Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.02971","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9fb6579b2eee1a13ec2b92e089db23034cb9feafa4d43d30fb57030af411fae0","sha256:4c2c1aad1867aae6209ab99c461ee57e32d5783fb1ad2b8e37eab5db71917a41"],"state_sha256":"684e957d0db47497330f5ace3ba4ee757bd451c3a9a3a74d7bce6332367b961a"}