{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YNCPHIAKRDM65WI4SNLBHHZ4QU","short_pith_number":"pith:YNCPHIAK","canonical_record":{"source":{"id":"2506.15719","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-03T20:33:08Z","cross_cats_sorted":[],"title_canon_sha256":"f2487f8861ce247aa1ef99619f76cffb2d8469365eb0cd5026892000377d988c","abstract_canon_sha256":"ecaae2e2c5c3db8245d5ebee647d775836a80b4bf3b4151b00aec47044864e55"},"schema_version":"1.0"},"canonical_sha256":"c344f3a00a88d9eed91c9356139f3c851e8a902f6c1f31d479bb6c117794c3a6","source":{"kind":"arxiv","id":"2506.15719","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.15719","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"arxiv_version","alias_value":"2506.15719v1","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.15719","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_12","alias_value":"YNCPHIAKRDM6","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_16","alias_value":"YNCPHIAKRDM65WI4","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_8","alias_value":"YNCPHIAK","created_at":"2026-07-05T11:23:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YNCPHIAKRDM65WI4SNLBHHZ4QU","target":"record","payload":{"canonical_record":{"source":{"id":"2506.15719","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-03T20:33:08Z","cross_cats_sorted":[],"title_canon_sha256":"f2487f8861ce247aa1ef99619f76cffb2d8469365eb0cd5026892000377d988c","abstract_canon_sha256":"ecaae2e2c5c3db8245d5ebee647d775836a80b4bf3b4151b00aec47044864e55"},"schema_version":"1.0"},"canonical_sha256":"c344f3a00a88d9eed91c9356139f3c851e8a902f6c1f31d479bb6c117794c3a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:23:51.069216Z","signature_b64":"oHSrJRgqKnIfE0gnOiDvWoII69NLThkmFyPLM1dV/sdSGZCGL7j0ClupkqiisON3wEP3fBn9bNb71xHUJZXNAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c344f3a00a88d9eed91c9356139f3c851e8a902f6c1f31d479bb6c117794c3a6","last_reissued_at":"2026-07-05T11:23:51.068720Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:23:51.068720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.15719","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":"2026-07-05T11:23:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dwxL/zP3bCrdqvAVl7rDJKdRpgh27eXrRpOW4Vp5URqTDh5KjkbecVxluSzOWRVRRrf7sY4S+7WIFYNOiCX7AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:56:59.317182Z"},"content_sha256":"8a0063dd695d35d8b68a9c9d22fcb6f49b3a3c74d0d594885a1969238baa4581","schema_version":"1.0","event_id":"sha256:8a0063dd695d35d8b68a9c9d22fcb6f49b3a3c74d0d594885a1969238baa4581"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YNCPHIAKRDM65WI4SNLBHHZ4QU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Albrecht Wurtz, Bestoun S. Ahmed, Manal Rahal, Robert Stener, Roger Renstrom","submitted_at":"2025-06-03T20:33:08Z","abstract_excerpt":"Heat pumps (HPs) have emerged as a cost-effective and clean technology for sustainable energy systems, but their efficiency in producing hot water remains restricted by conventional threshold-based control methods. Although machine learning (ML) has been successfully implemented for various HP applications, optimization of household hot water demand forecasting remains understudied. This paper addresses this problem by introducing a novel approach that combines predictive ML with anomaly detection to create adaptive hot water production strategies based on household-specific consumption patter"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.15719","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/2506.15719/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":"2026-07-05T11:23:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5QQUsV5EwRpzTf0vW5LlwHy18MQVxjDrYx2E4HIkwWu0Ijb5sLz+5yfSftMFzVqEC5nzntjRmWgyPWBpz8+YDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:56:59.317664Z"},"content_sha256":"5bfface7b58f5821491ce0c716957da859e6940e3f80ca2b56133b8b613c5eb1","schema_version":"1.0","event_id":"sha256:5bfface7b58f5821491ce0c716957da859e6940e3f80ca2b56133b8b613c5eb1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/bundle.json","state_url":"https://pith.science/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/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":"2026-08-08T13:56:59Z","links":{"resolver":"https://pith.science/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU","bundle":"https://pith.science/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/bundle.json","state":"https://pith.science/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YNCPHIAKRDM65WI4SNLBHHZ4QU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YNCPHIAKRDM65WI4SNLBHHZ4QU","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":"ecaae2e2c5c3db8245d5ebee647d775836a80b4bf3b4151b00aec47044864e55","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-03T20:33:08Z","title_canon_sha256":"f2487f8861ce247aa1ef99619f76cffb2d8469365eb0cd5026892000377d988c"},"schema_version":"1.0","source":{"id":"2506.15719","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.15719","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"arxiv_version","alias_value":"2506.15719v1","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.15719","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_12","alias_value":"YNCPHIAKRDM6","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_16","alias_value":"YNCPHIAKRDM65WI4","created_at":"2026-07-05T11:23:51Z"},{"alias_kind":"pith_short_8","alias_value":"YNCPHIAK","created_at":"2026-07-05T11:23:51Z"}],"graph_snapshots":[{"event_id":"sha256:5bfface7b58f5821491ce0c716957da859e6940e3f80ca2b56133b8b613c5eb1","target":"graph","created_at":"2026-07-05T11:23:51Z","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/2506.15719/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Heat pumps (HPs) have emerged as a cost-effective and clean technology for sustainable energy systems, but their efficiency in producing hot water remains restricted by conventional threshold-based control methods. Although machine learning (ML) has been successfully implemented for various HP applications, optimization of household hot water demand forecasting remains understudied. This paper addresses this problem by introducing a novel approach that combines predictive ML with anomaly detection to create adaptive hot water production strategies based on household-specific consumption patter","authors_text":"Albrecht Wurtz, Bestoun S. Ahmed, Manal Rahal, Robert Stener, Roger Renstrom","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-03T20:33:08Z","title":"Data-Driven Heat Pump Management: Combining Machine Learning with Anomaly Detection for Residential Hot Water Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.15719","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":"sha256:8a0063dd695d35d8b68a9c9d22fcb6f49b3a3c74d0d594885a1969238baa4581","target":"record","created_at":"2026-07-05T11:23:51Z","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":"ecaae2e2c5c3db8245d5ebee647d775836a80b4bf3b4151b00aec47044864e55","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-06-03T20:33:08Z","title_canon_sha256":"f2487f8861ce247aa1ef99619f76cffb2d8469365eb0cd5026892000377d988c"},"schema_version":"1.0","source":{"id":"2506.15719","kind":"arxiv","version":1}},"canonical_sha256":"c344f3a00a88d9eed91c9356139f3c851e8a902f6c1f31d479bb6c117794c3a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c344f3a00a88d9eed91c9356139f3c851e8a902f6c1f31d479bb6c117794c3a6","first_computed_at":"2026-07-05T11:23:51.068720Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:23:51.068720Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oHSrJRgqKnIfE0gnOiDvWoII69NLThkmFyPLM1dV/sdSGZCGL7j0ClupkqiisON3wEP3fBn9bNb71xHUJZXNAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:23:51.069216Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.15719","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8a0063dd695d35d8b68a9c9d22fcb6f49b3a3c74d0d594885a1969238baa4581","sha256:5bfface7b58f5821491ce0c716957da859e6940e3f80ca2b56133b8b613c5eb1"],"state_sha256":"c86630069ba71bb88901ad536d908bb0d44b1b00a6a433835abdc3ce7c216470"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g9F79KRBoTxcvPNm7qXgGe3/vyKcC4Nl2GD6ygxmJDyzni0K9IskWjPqPrc/SVcCzdIPgAQ9nWRNtx1fr9LOBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T13:56:59.320704Z","bundle_sha256":"15b1d31f378ecb6adad69f7267c033f1933e9c59c76acb5f338b7d92cc4b128b"}}