{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:74GGEPXLC736PJMQSWYOV23MNZ","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":"14e8e1f208fbedb1dbc99935f926063a58848ce06e8780b6d6913254dc8d93f2","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-16T17:03:04Z","title_canon_sha256":"9fce21741c5bc0933f0d8ff1e017bd16dd4007b61c6c8efff64e3db3c93e0744"},"schema_version":"1.0","source":{"id":"2412.11981","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11981","created_at":"2026-07-05T09:54:49Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11981v2","created_at":"2026-07-05T09:54:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11981","created_at":"2026-07-05T09:54:49Z"},{"alias_kind":"pith_short_12","alias_value":"74GGEPXLC736","created_at":"2026-07-05T09:54:49Z"},{"alias_kind":"pith_short_16","alias_value":"74GGEPXLC736PJMQ","created_at":"2026-07-05T09:54:49Z"},{"alias_kind":"pith_short_8","alias_value":"74GGEPXL","created_at":"2026-07-05T09:54:49Z"}],"graph_snapshots":[{"event_id":"sha256:ca064e6159cbdf60a82e9844d970bd3f65663afd3aaeb6ddb40ce5c327c4dfe1","target":"graph","created_at":"2026-07-05T09:54:49Z","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/2412.11981/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cement production, exceeding 4.1 billion tonnes and contributing 2.4 tonnes of CO2 annually, faces critical challenges in quality control and process optimization. While traditional process models for cement manufacturing are confined to steady-state conditions with limited predictive capability for mineralogical phases, modern plants operate under dynamic conditions that demand real-time quality assessment. Here, exploiting a comprehensive two-year operational dataset from an industrial cement plant, we present a machine learning framework that accurately predicts clinker mineralogy from proc","authors_text":"Manuele Gatti, Matteo Romano, Nestor Montiel-Bohorquez, N. M. Anoop Krishnan, Shashank Bishnoi, Sheikh Junaid Fayaz","cross_cats":["cond-mat.mtrl-sci"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-16T17:03:04Z","title":"Industrial-scale Prediction of Cement Clinker Phases using Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11981","kind":"arxiv","version":2},"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:f810ab1aed65920a096909d8b9d0b8731fd52bcad77f5ad5b4e74ce8b7fe46c8","target":"record","created_at":"2026-07-05T09:54:49Z","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":"14e8e1f208fbedb1dbc99935f926063a58848ce06e8780b6d6913254dc8d93f2","cross_cats_sorted":["cond-mat.mtrl-sci"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-16T17:03:04Z","title_canon_sha256":"9fce21741c5bc0933f0d8ff1e017bd16dd4007b61c6c8efff64e3db3c93e0744"},"schema_version":"1.0","source":{"id":"2412.11981","kind":"arxiv","version":2}},"canonical_sha256":"ff0c623eeb17f7e7a59095b0eaeb6c6e7ff2d27f64c789fe1fb9df6c418e4291","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff0c623eeb17f7e7a59095b0eaeb6c6e7ff2d27f64c789fe1fb9df6c418e4291","first_computed_at":"2026-07-05T09:54:49.209857Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:49.209857Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eSN9AE0aFMzh8x9XYFnNWADToe5XN9j5t7zpDFIc1tgaNsyQ13XCyUqvmd2H/wvJYIuJHeFTP7Z8hj61uu/vDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:49.210345Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.11981","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f810ab1aed65920a096909d8b9d0b8731fd52bcad77f5ad5b4e74ce8b7fe46c8","sha256:ca064e6159cbdf60a82e9844d970bd3f65663afd3aaeb6ddb40ce5c327c4dfe1"],"state_sha256":"235d4eeab24776b1a235f90c117eaedff21f5eb1e5604b0b4c7cc5670b5cc3dd"}