{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:IV5EJIFRUQAFNFFCUDOARYNYJJ","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":"5faf4aa8ca66801b403fe36752656c8faf6263ea0315fb465eac88046d835f56","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-01-17T23:05:14Z","title_canon_sha256":"b1286616ab2043643d93258d3790d94eb904edff59919fed1515f68d5b5eb2b1"},"schema_version":"1.0","source":{"id":"2201.06653","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2201.06653","created_at":"2026-07-05T03:49:00Z"},{"alias_kind":"arxiv_version","alias_value":"2201.06653v1","created_at":"2026-07-05T03:49:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.06653","created_at":"2026-07-05T03:49:00Z"},{"alias_kind":"pith_short_12","alias_value":"IV5EJIFRUQAF","created_at":"2026-07-05T03:49:00Z"},{"alias_kind":"pith_short_16","alias_value":"IV5EJIFRUQAFNFFC","created_at":"2026-07-05T03:49:00Z"},{"alias_kind":"pith_short_8","alias_value":"IV5EJIFR","created_at":"2026-07-05T03:49:00Z"}],"graph_snapshots":[{"event_id":"sha256:8b57632eed6749b0a0c96e140f73561924b79dc53f5099cbbdd49b8d281c410c","target":"graph","created_at":"2026-07-05T03:49:00Z","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/2201.06653/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning research typically starts with a fixed data set created early in the process. The focus of the experiments is finding a model and training procedure that result in the best possible performance in terms of some selected evaluation metric. This paper explores how changes in a data set influence the measured performance of a model. Using three publicly available data sets from the legal domain, we investigate how changes to their size, the train/test splits, and the human labelling accuracy impact the performance of a trained deep learning classifier. We assess the overall perfo","authors_text":"Hannes Westermann, Jaromir Savelka, Karim Benyekhlef, Kevin D. Ashley, Vern R. Walker","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-01-17T23:05:14Z","title":"Data-Centric Machine Learning in the Legal Domain"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.06653","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:ed6b73bcbe34afb220cbc93579b6cc1f1ed7c6d004e569b4f8c5ef6f817da577","target":"record","created_at":"2026-07-05T03:49:00Z","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":"5faf4aa8ca66801b403fe36752656c8faf6263ea0315fb465eac88046d835f56","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-01-17T23:05:14Z","title_canon_sha256":"b1286616ab2043643d93258d3790d94eb904edff59919fed1515f68d5b5eb2b1"},"schema_version":"1.0","source":{"id":"2201.06653","kind":"arxiv","version":1}},"canonical_sha256":"457a44a0b1a4005694a2a0dc08e1b84a7e418b018de126951ec4ed94ac5975e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"457a44a0b1a4005694a2a0dc08e1b84a7e418b018de126951ec4ed94ac5975e6","first_computed_at":"2026-07-05T03:49:00.374394Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:49:00.374394Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9o/bqleAL3J07Rw8cyLKzmBknAE4UNFKUsgr56yxUK1L831GH25N1FrSYeL8DMK3DNBVcrDmz5OmWlLPzC7+BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:49:00.374805Z","signed_message":"canonical_sha256_bytes"},"source_id":"2201.06653","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ed6b73bcbe34afb220cbc93579b6cc1f1ed7c6d004e569b4f8c5ef6f817da577","sha256:8b57632eed6749b0a0c96e140f73561924b79dc53f5099cbbdd49b8d281c410c"],"state_sha256":"21589e7e526e8a9369e75e281ca36db79784071120a4c96fa363b5a7a076fb2e"}