{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IFH3MFE4KKX64HT2OEVJXKG2G6","short_pith_number":"pith:IFH3MFE4","canonical_record":{"source":{"id":"2504.07007","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-04-09T16:26:21Z","cross_cats_sorted":[],"title_canon_sha256":"90894e8b724d868da120191a31867ee13459532393c062485572243c07a8fc06","abstract_canon_sha256":"b3ad3ef7f8deba2a9f32c3684a5dfbf2b4cdeb0b05c3545dedbdd20cd31ce347"},"schema_version":"1.0"},"canonical_sha256":"414fb6149c52afee1e7a712a9ba8da3793d4fd13e4cd8eb5b6a75d26b974352b","source":{"kind":"arxiv","id":"2504.07007","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.07007","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"arxiv_version","alias_value":"2504.07007v1","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.07007","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_12","alias_value":"IFH3MFE4KKX6","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_16","alias_value":"IFH3MFE4KKX64HT2","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_8","alias_value":"IFH3MFE4","created_at":"2026-07-05T10:46:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IFH3MFE4KKX64HT2OEVJXKG2G6","target":"record","payload":{"canonical_record":{"source":{"id":"2504.07007","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-04-09T16:26:21Z","cross_cats_sorted":[],"title_canon_sha256":"90894e8b724d868da120191a31867ee13459532393c062485572243c07a8fc06","abstract_canon_sha256":"b3ad3ef7f8deba2a9f32c3684a5dfbf2b4cdeb0b05c3545dedbdd20cd31ce347"},"schema_version":"1.0"},"canonical_sha256":"414fb6149c52afee1e7a712a9ba8da3793d4fd13e4cd8eb5b6a75d26b974352b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:46:49.780565Z","signature_b64":"22O1Nc+Szxk6AqCrBkEPFK5hFnVHfpWnVZIp/35QFvnusDGDYLB9rx0fG/vIfEGFJegaAK6DOCFfESRtMYBDAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"414fb6149c52afee1e7a712a9ba8da3793d4fd13e4cd8eb5b6a75d26b974352b","last_reissued_at":"2026-07-05T10:46:49.780070Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:46:49.780070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.07007","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":"2026-07-05T10:46:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fBGK+LLS6YXNDFSSg27UUpKyHls7tpUmN51z71QNg2JSboVNt8HCyY7LtieCmdT4Xx+WKFFrtj+SQaNKswLoBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:38:19.726633Z"},"content_sha256":"72714e166b0872c98ae7a172d12c2116ad0c11387eb0008e2570595769c3c873","schema_version":"1.0","event_id":"sha256:72714e166b0872c98ae7a172d12c2116ad0c11387eb0008e2570595769c3c873"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IFH3MFE4KKX64HT2OEVJXKG2G6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Juejing Liu, Kevin M. Rosso, Xiaofeng Guo, Xiaoxu Li, Xin Zhang, Yifu Feng, Zheming Wang","submitted_at":"2025-04-09T16:26:21Z","abstract_excerpt":"Quantitative understanding of rare earth element (REE) mineralization mechanisms, crucial for improving industrial separation, remains limited. This study leverages 1239 hydrothermal synthesis datapoints from material science as a surrogate for natural REE mineralization. We trained machine learning models (KNN, RF, XGBoost) using precursor, additive, and reaction data to predict product elements and phases, validating predictions with new experiments. XGBoost exhibited the highest accuracy, with feature importance analysis indicating thermodynamic properties were critical for predictions. Obs"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.07007","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/2504.07007/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":"2026-07-05T10:46:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xikK/+FEq5pABFE4enFsqCjZdmjeXKbWJf8jCjaGMwMudmfYaExp4S4L57Ki7xX54xNpGSDRT7UB5XH0h66jCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:38:19.727000Z"},"content_sha256":"80dd1ee4160680a61296a3a4a2f71e8eebc839ce5cde0fd16e0a92ed64056d2a","schema_version":"1.0","event_id":"sha256:80dd1ee4160680a61296a3a4a2f71e8eebc839ce5cde0fd16e0a92ed64056d2a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/bundle.json","state_url":"https://pith.science/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/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":"2026-07-06T18:38:19Z","links":{"resolver":"https://pith.science/pith/IFH3MFE4KKX64HT2OEVJXKG2G6","bundle":"https://pith.science/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/bundle.json","state":"https://pith.science/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IFH3MFE4KKX64HT2OEVJXKG2G6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IFH3MFE4KKX64HT2OEVJXKG2G6","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":"b3ad3ef7f8deba2a9f32c3684a5dfbf2b4cdeb0b05c3545dedbdd20cd31ce347","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-04-09T16:26:21Z","title_canon_sha256":"90894e8b724d868da120191a31867ee13459532393c062485572243c07a8fc06"},"schema_version":"1.0","source":{"id":"2504.07007","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.07007","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"arxiv_version","alias_value":"2504.07007v1","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.07007","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_12","alias_value":"IFH3MFE4KKX6","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_16","alias_value":"IFH3MFE4KKX64HT2","created_at":"2026-07-05T10:46:49Z"},{"alias_kind":"pith_short_8","alias_value":"IFH3MFE4","created_at":"2026-07-05T10:46:49Z"}],"graph_snapshots":[{"event_id":"sha256:80dd1ee4160680a61296a3a4a2f71e8eebc839ce5cde0fd16e0a92ed64056d2a","target":"graph","created_at":"2026-07-05T10:46:49Z","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/2504.07007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantitative understanding of rare earth element (REE) mineralization mechanisms, crucial for improving industrial separation, remains limited. This study leverages 1239 hydrothermal synthesis datapoints from material science as a surrogate for natural REE mineralization. We trained machine learning models (KNN, RF, XGBoost) using precursor, additive, and reaction data to predict product elements and phases, validating predictions with new experiments. XGBoost exhibited the highest accuracy, with feature importance analysis indicating thermodynamic properties were critical for predictions. Obs","authors_text":"Juejing Liu, Kevin M. Rosso, Xiaofeng Guo, Xiaoxu Li, Xin Zhang, Yifu Feng, Zheming Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-04-09T16:26:21Z","title":"Data-Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.07007","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":"sha256:72714e166b0872c98ae7a172d12c2116ad0c11387eb0008e2570595769c3c873","target":"record","created_at":"2026-07-05T10:46:49Z","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":"b3ad3ef7f8deba2a9f32c3684a5dfbf2b4cdeb0b05c3545dedbdd20cd31ce347","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-04-09T16:26:21Z","title_canon_sha256":"90894e8b724d868da120191a31867ee13459532393c062485572243c07a8fc06"},"schema_version":"1.0","source":{"id":"2504.07007","kind":"arxiv","version":1}},"canonical_sha256":"414fb6149c52afee1e7a712a9ba8da3793d4fd13e4cd8eb5b6a75d26b974352b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"414fb6149c52afee1e7a712a9ba8da3793d4fd13e4cd8eb5b6a75d26b974352b","first_computed_at":"2026-07-05T10:46:49.780070Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:46:49.780070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"22O1Nc+Szxk6AqCrBkEPFK5hFnVHfpWnVZIp/35QFvnusDGDYLB9rx0fG/vIfEGFJegaAK6DOCFfESRtMYBDAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:46:49.780565Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.07007","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:72714e166b0872c98ae7a172d12c2116ad0c11387eb0008e2570595769c3c873","sha256:80dd1ee4160680a61296a3a4a2f71e8eebc839ce5cde0fd16e0a92ed64056d2a"],"state_sha256":"45c46bcc10f9b6accf97fd5437cb38093701a2a7e97c3d5da74eef50e082404e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E8lZhHo8cFxb2fFm71XHqLMVugKiM9BU0m+SHM6SNQCuRt91Q0ryiQjl7TOiErrtOt/SEjVJ2w5710e5gP/mDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:38:19.728860Z","bundle_sha256":"9e4978b269ff422396e555a1ddaf3cb444b3714f006ec888a89041a7a4b5bfa9"}}