{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:E6Y2Q6LR5IQMJ3NS6BCX3WK6XX","short_pith_number":"pith:E6Y2Q6LR","canonical_record":{"source":{"id":"2308.08934","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-17T12:04:14Z","cross_cats_sorted":["cond-mat.mtrl-sci"],"title_canon_sha256":"fa859dfaa07a88308e243cb463a976d626b4d5ede93f9af319d4c8d0541a7ff7","abstract_canon_sha256":"ab1b15cf35d232d6ed0efd325e78b7af651a3054c1408cf07d5a3dce856cee7b"},"schema_version":"1.0"},"canonical_sha256":"27b1a87971ea20c4edb2f0457dd95ebdd7b97fed7ea3dad9934baa665675a83a","source":{"kind":"arxiv","id":"2308.08934","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.08934","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"arxiv_version","alias_value":"2308.08934v1","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.08934","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_12","alias_value":"E6Y2Q6LR5IQM","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_16","alias_value":"E6Y2Q6LR5IQMJ3NS","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_8","alias_value":"E6Y2Q6LR","created_at":"2026-07-05T06:42:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:E6Y2Q6LR5IQMJ3NS6BCX3WK6XX","target":"record","payload":{"canonical_record":{"source":{"id":"2308.08934","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-17T12:04:14Z","cross_cats_sorted":["cond-mat.mtrl-sci"],"title_canon_sha256":"fa859dfaa07a88308e243cb463a976d626b4d5ede93f9af319d4c8d0541a7ff7","abstract_canon_sha256":"ab1b15cf35d232d6ed0efd325e78b7af651a3054c1408cf07d5a3dce856cee7b"},"schema_version":"1.0"},"canonical_sha256":"27b1a87971ea20c4edb2f0457dd95ebdd7b97fed7ea3dad9934baa665675a83a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:42:13.552110Z","signature_b64":"NK6salrdCsYnsuUwqLOPGJhJaqkJsYVJAN0HT6YydJ6YL26O9nlZyd7sQACCvIVg3DSXiulytCmsUB/EZRvfBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27b1a87971ea20c4edb2f0457dd95ebdd7b97fed7ea3dad9934baa665675a83a","last_reissued_at":"2026-07-05T06:42:13.551629Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:42:13.551629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.08934","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:42:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZbHi8zB/tuhBiJc9uZZWvk3pYYZtRo0ud/S8EK+XsgkJj0vHHBE1r1BchZtuyTNn+c1cJ47yk2o0lAbEwWfqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T00:01:45.863503Z"},"content_sha256":"137528eb9973d81a4e6dfccd12c37bb4e073ab58e98e7ba93036b4039e6b4526","schema_version":"1.0","event_id":"sha256:137528eb9973d81a4e6dfccd12c37bb4e073ab58e98e7ba93036b4039e6b4526"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:E6Y2Q6LR5IQMJ3NS6BCX3WK6XX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Data Imbalance in Molecular Property Prediction with Pre-training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.mtrl-sci"],"primary_cat":"cs.LG","authors_text":"Kenjiro Taura, Limin Wang, Masatoshi Hanai, Shun Takashige, Toyotaro Suzumura","submitted_at":"2023-08-17T12:04:14Z","abstract_excerpt":"Revealing and analyzing the various properties of materials is an essential and critical issue in the development of materials, including batteries, semiconductors, catalysts, and pharmaceuticals. Traditionally, these properties have been determined through theoretical calculations and simulations. However, it is not practical to perform such calculations on every single candidate material. Recently, a combination method of the theoretical calculation and machine learning has emerged, that involves training machine learning models on a subset of theoretical calculation results to construct a s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.08934","kind":"arxiv","version":1},"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/2308.08934/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":"2026-07-05T06:42:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9dOom2WdPJIImYKiAZkeWrdtf4gVQ+Z75pNiPO8WM/3eS+tQCHqG4OC5F8ZcvVqZro1XI1tJj2w0uLCoXZfSBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T00:01:45.863896Z"},"content_sha256":"aa756ccc38296d1e98e56939753624014a52a1a6b1cd874df288647466c308ad","schema_version":"1.0","event_id":"sha256:aa756ccc38296d1e98e56939753624014a52a1a6b1cd874df288647466c308ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/bundle.json","state_url":"https://pith.science/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/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":"2026-08-14T00:01:45Z","links":{"resolver":"https://pith.science/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX","bundle":"https://pith.science/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/bundle.json","state":"https://pith.science/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E6Y2Q6LR5IQMJ3NS6BCX3WK6XX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:E6Y2Q6LR5IQMJ3NS6BCX3WK6XX","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":"ab1b15cf35d232d6ed0efd325e78b7af651a3054c1408cf07d5a3dce856cee7b","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-17T12:04:14Z","title_canon_sha256":"fa859dfaa07a88308e243cb463a976d626b4d5ede93f9af319d4c8d0541a7ff7"},"schema_version":"1.0","source":{"id":"2308.08934","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.08934","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"arxiv_version","alias_value":"2308.08934v1","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.08934","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_12","alias_value":"E6Y2Q6LR5IQM","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_16","alias_value":"E6Y2Q6LR5IQMJ3NS","created_at":"2026-07-05T06:42:13Z"},{"alias_kind":"pith_short_8","alias_value":"E6Y2Q6LR","created_at":"2026-07-05T06:42:13Z"}],"graph_snapshots":[{"event_id":"sha256:aa756ccc38296d1e98e56939753624014a52a1a6b1cd874df288647466c308ad","target":"graph","created_at":"2026-07-05T06:42:13Z","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/2308.08934/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Revealing and analyzing the various properties of materials is an essential and critical issue in the development of materials, including batteries, semiconductors, catalysts, and pharmaceuticals. Traditionally, these properties have been determined through theoretical calculations and simulations. However, it is not practical to perform such calculations on every single candidate material. Recently, a combination method of the theoretical calculation and machine learning has emerged, that involves training machine learning models on a subset of theoretical calculation results to construct a s","authors_text":"Kenjiro Taura, Limin Wang, Masatoshi Hanai, Shun Takashige, Toyotaro Suzumura","cross_cats":["cond-mat.mtrl-sci"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-17T12:04:14Z","title":"On Data Imbalance in Molecular Property Prediction with Pre-training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.08934","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":"sha256:137528eb9973d81a4e6dfccd12c37bb4e073ab58e98e7ba93036b4039e6b4526","target":"record","created_at":"2026-07-05T06:42:13Z","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":"ab1b15cf35d232d6ed0efd325e78b7af651a3054c1408cf07d5a3dce856cee7b","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-08-17T12:04:14Z","title_canon_sha256":"fa859dfaa07a88308e243cb463a976d626b4d5ede93f9af319d4c8d0541a7ff7"},"schema_version":"1.0","source":{"id":"2308.08934","kind":"arxiv","version":1}},"canonical_sha256":"27b1a87971ea20c4edb2f0457dd95ebdd7b97fed7ea3dad9934baa665675a83a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27b1a87971ea20c4edb2f0457dd95ebdd7b97fed7ea3dad9934baa665675a83a","first_computed_at":"2026-07-05T06:42:13.551629Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:42:13.551629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NK6salrdCsYnsuUwqLOPGJhJaqkJsYVJAN0HT6YydJ6YL26O9nlZyd7sQACCvIVg3DSXiulytCmsUB/EZRvfBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:42:13.552110Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.08934","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:137528eb9973d81a4e6dfccd12c37bb4e073ab58e98e7ba93036b4039e6b4526","sha256:aa756ccc38296d1e98e56939753624014a52a1a6b1cd874df288647466c308ad"],"state_sha256":"a020502cd0581f6adf0971ff37f1a049c9fef3d75122213e39b6167c21221600"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"92tcEwn79Ds8new7o+wK5pip6KKbVN2v7e0LjOKabhb1+dvsDGvEdsobeHCtfYswqk/qF4Ze0p43hbQyW4UACA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T00:01:45.867099Z","bundle_sha256":"cadca80d3fcb772c619bfbeb07c0c2043f4f95e01bdcba8e82fcbf50fca2f93f"}}