{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KAYZB5EUKVOEVNLXS3WK6SSBIS","short_pith_number":"pith:KAYZB5EU","canonical_record":{"source":{"id":"1902.09426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-02-22T14:12:28Z","cross_cats_sorted":["cs.LG","cs.SY","stat.ML"],"title_canon_sha256":"7ae118c009faf2ddbc06b64010bfc9536d79f9f485fc092057338fb60d362e74","abstract_canon_sha256":"35ff8d289a8f86c05d669bdb7271d7ede9f5d5a330ace6838bb0a374aeee5615"},"schema_version":"1.0"},"canonical_sha256":"503190f494555c4ab57796ecaf4a4144bd6e94b6686fdf8e44af7bb6b0242dc3","source":{"kind":"arxiv","id":"1902.09426","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09426","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09426v1","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09426","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"pith_short_12","alias_value":"KAYZB5EUKVOE","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KAYZB5EUKVOEVNLX","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KAYZB5EU","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KAYZB5EUKVOEVNLXS3WK6SSBIS","target":"record","payload":{"canonical_record":{"source":{"id":"1902.09426","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-02-22T14:12:28Z","cross_cats_sorted":["cs.LG","cs.SY","stat.ML"],"title_canon_sha256":"7ae118c009faf2ddbc06b64010bfc9536d79f9f485fc092057338fb60d362e74","abstract_canon_sha256":"35ff8d289a8f86c05d669bdb7271d7ede9f5d5a330ace6838bb0a374aeee5615"},"schema_version":"1.0"},"canonical_sha256":"503190f494555c4ab57796ecaf4a4144bd6e94b6686fdf8e44af7bb6b0242dc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:52:45.806154Z","signature_b64":"avKKVAvy91+4X+/YtpMHCer1GkdNE2AIiTEchGdFMYcVPiBAjz2mFNJ7/KKEAsg1KNVp5mri1LsTjciwNUobBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"503190f494555c4ab57796ecaf4a4144bd6e94b6686fdf8e44af7bb6b0242dc3","last_reissued_at":"2026-05-17T23:52:45.805619Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:52:45.805619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.09426","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":"2026-05-17T23:52:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gdk/R67RTVGTNUH2KgxKA8pPXqvq3mkgec8aCjB3ZgWkcgwjr4I3rLMAa8Ezpfqhin6p9DZlLZfYjGlzUEhaAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T14:12:15.510870Z"},"content_sha256":"0dd6d1f713efa4affec90f0bcf84ed24a3c83f6f9befc44d750ba10fe83a806f","schema_version":"1.0","event_id":"sha256:0dd6d1f713efa4affec90f0bcf84ed24a3c83f6f9befc44d750ba10fe83a806f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KAYZB5EUKVOEVNLXS3WK6SSBIS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semi-supervised Approach to Soft Sensor Modeling for Fault Detection in Industrial Systems with Multiple Operation Modes","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SY","stat.ML"],"primary_cat":"eess.SP","authors_text":"Isamu Watanabe, Shun Takeuchi, Takahiro Saito, Takuya Nishino","submitted_at":"2019-02-22T14:12:28Z","abstract_excerpt":"In industrial systems, certain process variables that need to be monitored for detecting faults are often difficult or impossible to measure. Soft sensor techniques are widely used to estimate such difficult-to-measure process variables from easy-to-measure ones. Soft sensor modeling requires training datasets including the information of various states such as operation modes, but the fault dataset with the target variable is insufficient as the training dataset. This paper describes a semi-supervised approach to soft sensor modeling to incorporate an incomplete dataset without the target var"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09426","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":""},"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":"2026-05-17T23:52:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rYHvCpY5UIej7Ewaav+eVFfqRIIhA2vw1Qdj3z5lhQf/dxxACnlwZEEoOFm0TNUIELjAcZ7q1kzXE8onrs7sCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T14:12:15.511210Z"},"content_sha256":"b76f335601430bdc25fe1a3e7ca98b20029baa679323c93634a1eb5aeca91d76","schema_version":"1.0","event_id":"sha256:b76f335601430bdc25fe1a3e7ca98b20029baa679323c93634a1eb5aeca91d76"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/bundle.json","state_url":"https://pith.science/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/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":"2026-06-26T14:12:15Z","links":{"resolver":"https://pith.science/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS","bundle":"https://pith.science/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/bundle.json","state":"https://pith.science/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KAYZB5EUKVOEVNLXS3WK6SSBIS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KAYZB5EUKVOEVNLXS3WK6SSBIS","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":"35ff8d289a8f86c05d669bdb7271d7ede9f5d5a330ace6838bb0a374aeee5615","cross_cats_sorted":["cs.LG","cs.SY","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-02-22T14:12:28Z","title_canon_sha256":"7ae118c009faf2ddbc06b64010bfc9536d79f9f485fc092057338fb60d362e74"},"schema_version":"1.0","source":{"id":"1902.09426","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.09426","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"arxiv_version","alias_value":"1902.09426v1","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.09426","created_at":"2026-05-17T23:52:45Z"},{"alias_kind":"pith_short_12","alias_value":"KAYZB5EUKVOE","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KAYZB5EUKVOEVNLX","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KAYZB5EU","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:b76f335601430bdc25fe1a3e7ca98b20029baa679323c93634a1eb5aeca91d76","target":"graph","created_at":"2026-05-17T23:52:45Z","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"},"paper":{"abstract_excerpt":"In industrial systems, certain process variables that need to be monitored for detecting faults are often difficult or impossible to measure. Soft sensor techniques are widely used to estimate such difficult-to-measure process variables from easy-to-measure ones. Soft sensor modeling requires training datasets including the information of various states such as operation modes, but the fault dataset with the target variable is insufficient as the training dataset. This paper describes a semi-supervised approach to soft sensor modeling to incorporate an incomplete dataset without the target var","authors_text":"Isamu Watanabe, Shun Takeuchi, Takahiro Saito, Takuya Nishino","cross_cats":["cs.LG","cs.SY","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-02-22T14:12:28Z","title":"Semi-supervised Approach to Soft Sensor Modeling for Fault Detection in Industrial Systems with Multiple Operation Modes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.09426","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":"sha256:0dd6d1f713efa4affec90f0bcf84ed24a3c83f6f9befc44d750ba10fe83a806f","target":"record","created_at":"2026-05-17T23:52:45Z","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":"35ff8d289a8f86c05d669bdb7271d7ede9f5d5a330ace6838bb0a374aeee5615","cross_cats_sorted":["cs.LG","cs.SY","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-02-22T14:12:28Z","title_canon_sha256":"7ae118c009faf2ddbc06b64010bfc9536d79f9f485fc092057338fb60d362e74"},"schema_version":"1.0","source":{"id":"1902.09426","kind":"arxiv","version":1}},"canonical_sha256":"503190f494555c4ab57796ecaf4a4144bd6e94b6686fdf8e44af7bb6b0242dc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"503190f494555c4ab57796ecaf4a4144bd6e94b6686fdf8e44af7bb6b0242dc3","first_computed_at":"2026-05-17T23:52:45.805619Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:52:45.805619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"avKKVAvy91+4X+/YtpMHCer1GkdNE2AIiTEchGdFMYcVPiBAjz2mFNJ7/KKEAsg1KNVp5mri1LsTjciwNUobBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:52:45.806154Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.09426","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dd6d1f713efa4affec90f0bcf84ed24a3c83f6f9befc44d750ba10fe83a806f","sha256:b76f335601430bdc25fe1a3e7ca98b20029baa679323c93634a1eb5aeca91d76"],"state_sha256":"ac7689568ed83882e043fa7b5c8bd4ea487a31451eef1a1e41e834e7fa9e4528"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2OENn4MlLG8lHQ3T7LFYnTXEKfuQI4UEecar844xJo3Cpb636NXIRN2sbN4NhBOjNJgiO7lLc/sJql+lqz+uBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T14:12:15.513234Z","bundle_sha256":"f93982bc85288c62acd18aeff3c861fd3baf9b97ec8c0641eedea7b5f733e7b2"}}