{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:X356A7NUYKI7OM2GO4ER5NIWXI","short_pith_number":"pith:X356A7NU","canonical_record":{"source":{"id":"2211.00558","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-01T16:12:42Z","cross_cats_sorted":[],"title_canon_sha256":"e9e6c0bacc1c206b24e71a9ecb1c25411942c52824d83f2e9a5ab090be6b2e6c","abstract_canon_sha256":"ef1a5908b938f311b7450ce3c3c2af87239b0f487d30ec5327b5ab5b8b559878"},"schema_version":"1.0"},"canonical_sha256":"befbe07db4c291f7334677091eb516ba07bda60b59921f2a151a91367a9cfa10","source":{"kind":"arxiv","id":"2211.00558","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00558","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00558v1","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00558","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_12","alias_value":"X356A7NUYKI7","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_16","alias_value":"X356A7NUYKI7OM2G","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_8","alias_value":"X356A7NU","created_at":"2026-07-05T05:12:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:X356A7NUYKI7OM2GO4ER5NIWXI","target":"record","payload":{"canonical_record":{"source":{"id":"2211.00558","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-01T16:12:42Z","cross_cats_sorted":[],"title_canon_sha256":"e9e6c0bacc1c206b24e71a9ecb1c25411942c52824d83f2e9a5ab090be6b2e6c","abstract_canon_sha256":"ef1a5908b938f311b7450ce3c3c2af87239b0f487d30ec5327b5ab5b8b559878"},"schema_version":"1.0"},"canonical_sha256":"befbe07db4c291f7334677091eb516ba07bda60b59921f2a151a91367a9cfa10","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:12:24.147620Z","signature_b64":"WWavvWpAWYETo2de2n7ffQdSiGjlcRpOXUmRkRAkAggrH6Q8EfjZwvVbaf9i+cM3LqbyFlYmFfyQCaIXywV1AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"befbe07db4c291f7334677091eb516ba07bda60b59921f2a151a91367a9cfa10","last_reissued_at":"2026-07-05T05:12:24.147214Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:12:24.147214Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.00558","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":"2026-07-05T05:12:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dt5We71C74/eOWQmsYwrBweCwQieQCVkxNwkBuHi1yghtx+CUF2M8v4FVno4hd2Bea0cFzph/LGeBCMROtGnDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:11:27.423266Z"},"content_sha256":"612b0f2f1fccfc21423e7133b79fbdac8a432f1b619a88ee56cc9bdca6b0a7ef","schema_version":"1.0","event_id":"sha256:612b0f2f1fccfc21423e7133b79fbdac8a432f1b619a88ee56cc9bdca6b0a7ef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:X356A7NUYKI7OM2GO4ER5NIWXI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Francisco Souza, Geert Postma, Jeroen Jansen, Ruud Barendse, Tim Offermans","submitted_at":"2022-11-01T16:12:42Z","abstract_excerpt":"This work proposes a new data-driven model devised to integrate process knowledge into its structure to increase the human-machine synergy in the process industry. The proposed Contextual Mixture of Experts (cMoE) explicitly uses process knowledge along the model learning stage to mold the historical data to represent operators' context related to the process through possibility distributions. This model was evaluated in two real case studies for quality prediction, including a sulfur recovery unit and a polymerization process. The contextual mixture of experts was employed to represent differ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00558","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/2211.00558/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":"2026-07-05T05:12:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WWEOiFU46JJBuYmS6R3eJSc0dmXEcUXb18suCn1WexdMd0SF6MHMpkbtJcgSy5P3mUKN3drLwDq+1rUWuIe1Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:11:27.423769Z"},"content_sha256":"67365f33b406d2ae6ddf8b10c7870074fabcecac0edc1098484ba70246151d6a","schema_version":"1.0","event_id":"sha256:67365f33b406d2ae6ddf8b10c7870074fabcecac0edc1098484ba70246151d6a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X356A7NUYKI7OM2GO4ER5NIWXI/bundle.json","state_url":"https://pith.science/pith/X356A7NUYKI7OM2GO4ER5NIWXI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X356A7NUYKI7OM2GO4ER5NIWXI/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":"2026-08-19T03:11:27Z","links":{"resolver":"https://pith.science/pith/X356A7NUYKI7OM2GO4ER5NIWXI","bundle":"https://pith.science/pith/X356A7NUYKI7OM2GO4ER5NIWXI/bundle.json","state":"https://pith.science/pith/X356A7NUYKI7OM2GO4ER5NIWXI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X356A7NUYKI7OM2GO4ER5NIWXI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:X356A7NUYKI7OM2GO4ER5NIWXI","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":"ef1a5908b938f311b7450ce3c3c2af87239b0f487d30ec5327b5ab5b8b559878","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-01T16:12:42Z","title_canon_sha256":"e9e6c0bacc1c206b24e71a9ecb1c25411942c52824d83f2e9a5ab090be6b2e6c"},"schema_version":"1.0","source":{"id":"2211.00558","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00558","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00558v1","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00558","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_12","alias_value":"X356A7NUYKI7","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_16","alias_value":"X356A7NUYKI7OM2G","created_at":"2026-07-05T05:12:24Z"},{"alias_kind":"pith_short_8","alias_value":"X356A7NU","created_at":"2026-07-05T05:12:24Z"}],"graph_snapshots":[{"event_id":"sha256:67365f33b406d2ae6ddf8b10c7870074fabcecac0edc1098484ba70246151d6a","target":"graph","created_at":"2026-07-05T05:12:24Z","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/2211.00558/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work proposes a new data-driven model devised to integrate process knowledge into its structure to increase the human-machine synergy in the process industry. The proposed Contextual Mixture of Experts (cMoE) explicitly uses process knowledge along the model learning stage to mold the historical data to represent operators' context related to the process through possibility distributions. This model was evaluated in two real case studies for quality prediction, including a sulfur recovery unit and a polymerization process. The contextual mixture of experts was employed to represent differ","authors_text":"Francisco Souza, Geert Postma, Jeroen Jansen, Ruud Barendse, Tim Offermans","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-01T16:12:42Z","title":"Contextual Mixture of Experts: Integrating Knowledge into Predictive Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00558","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":"sha256:612b0f2f1fccfc21423e7133b79fbdac8a432f1b619a88ee56cc9bdca6b0a7ef","target":"record","created_at":"2026-07-05T05:12:24Z","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":"ef1a5908b938f311b7450ce3c3c2af87239b0f487d30ec5327b5ab5b8b559878","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2022-11-01T16:12:42Z","title_canon_sha256":"e9e6c0bacc1c206b24e71a9ecb1c25411942c52824d83f2e9a5ab090be6b2e6c"},"schema_version":"1.0","source":{"id":"2211.00558","kind":"arxiv","version":1}},"canonical_sha256":"befbe07db4c291f7334677091eb516ba07bda60b59921f2a151a91367a9cfa10","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"befbe07db4c291f7334677091eb516ba07bda60b59921f2a151a91367a9cfa10","first_computed_at":"2026-07-05T05:12:24.147214Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:12:24.147214Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WWavvWpAWYETo2de2n7ffQdSiGjlcRpOXUmRkRAkAggrH6Q8EfjZwvVbaf9i+cM3LqbyFlYmFfyQCaIXywV1AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:12:24.147620Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.00558","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:612b0f2f1fccfc21423e7133b79fbdac8a432f1b619a88ee56cc9bdca6b0a7ef","sha256:67365f33b406d2ae6ddf8b10c7870074fabcecac0edc1098484ba70246151d6a"],"state_sha256":"8d16f1252f3c17ed8b6b815aa619b5b33baa46ec4ec2b8b75f9d050c5e0871da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5obBkXIIzzjMeFWNVz/xSVa3O5Le+8vZeF4sNjC0apFbtntCgg2mGyv7hxRj/f/pkx4L1XFhLv6HV/xttnd+Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T03:11:27.427420Z","bundle_sha256":"862f94d07266743adf59efbaea03635136fb38e0b617d804cdf94afaeb5dd495"}}