{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:E75OD2V7CWWXNX4XRBEALILZ2N","short_pith_number":"pith:E75OD2V7","canonical_record":{"source":{"id":"1409.4119","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-09-14T23:26:31Z","cross_cats_sorted":[],"title_canon_sha256":"f43f75ac30c2bea0ad33a9be5c237e2f6c7925e571ca2307915dbde9c8c8f731","abstract_canon_sha256":"576b914b576ad30b2cdaf991f4c82fffe7a884b611c0f6567f7f53d0bd8f05ad"},"schema_version":"1.0"},"canonical_sha256":"27fae1eabf15ad76df97884805a179d347876499e09206141796c405bffffcd1","source":{"kind":"arxiv","id":"1409.4119","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1409.4119","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"arxiv_version","alias_value":"1409.4119v1","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.4119","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"pith_short_12","alias_value":"E75OD2V7CWWX","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"E75OD2V7CWWXNX4X","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"E75OD2V7","created_at":"2026-05-18T12:28:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:E75OD2V7CWWXNX4XRBEALILZ2N","target":"record","payload":{"canonical_record":{"source":{"id":"1409.4119","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-09-14T23:26:31Z","cross_cats_sorted":[],"title_canon_sha256":"f43f75ac30c2bea0ad33a9be5c237e2f6c7925e571ca2307915dbde9c8c8f731","abstract_canon_sha256":"576b914b576ad30b2cdaf991f4c82fffe7a884b611c0f6567f7f53d0bd8f05ad"},"schema_version":"1.0"},"canonical_sha256":"27fae1eabf15ad76df97884805a179d347876499e09206141796c405bffffcd1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:42:53.010156Z","signature_b64":"XlGJZ8H7s7TJQtUqjS/A7rliv1iHzYlrJxaB2mCt9d442y/MeBXMRD+Ki/8moYnlne7BPp/9DdiCQoF3K48uBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27fae1eabf15ad76df97884805a179d347876499e09206141796c405bffffcd1","last_reissued_at":"2026-05-18T02:42:53.009755Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:42:53.009755Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1409.4119","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":"2026-05-18T02:42:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CXoB5/Lum3+N8X3fALv6R6+8e3TngiYUcptCnaxO9gK/i5ZziP83pC6FmxvVpZ/ADB8+7z61Uu7XpCjHcnAvBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T16:50:45.184653Z"},"content_sha256":"59789e4e8e37b9536a83a89818ccfee661696d1721347a1b16b61e4672d9ccaa","schema_version":"1.0","event_id":"sha256:59789e4e8e37b9536a83a89818ccfee661696d1721347a1b16b61e4672d9ccaa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:E75OD2V7CWWXNX4XRBEALILZ2N","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Targeting Customers for Demand Response Based on Big Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Jungsuk Kwac, Ram Rajagopal","submitted_at":"2014-09-14T23:26:31Z","abstract_excerpt":"Selecting customers for demand response programs is challenging and existing methodologies are hard to scale and poor in performance. The existing methods were limited by lack of temporal consumption information at the individual customer level. We propose a scalable methodology for demand response targeting utilizing novel data available from smart meters. The approach relies on formulating the problem as a stochastic integer program involving predicted customer responses. A novel approximation is developed algorithm so it can scale to problems involving millions of customers. The methodology"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.4119","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":"2026-05-18T02:42:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CzU+sSfIqkPglMkjQujrc75ADJIE6vou81JJ/BsQ+DSyKoWrR1m458T7CS2hhiqUM2EnwAUa9CYxe1Pa6VhOCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T16:50:45.185003Z"},"content_sha256":"649537e83568c20603dc06c8bfa97f8a4269ca5c4f7123d9d26ebe5228b195bb","schema_version":"1.0","event_id":"sha256:649537e83568c20603dc06c8bfa97f8a4269ca5c4f7123d9d26ebe5228b195bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E75OD2V7CWWXNX4XRBEALILZ2N/bundle.json","state_url":"https://pith.science/pith/E75OD2V7CWWXNX4XRBEALILZ2N/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E75OD2V7CWWXNX4XRBEALILZ2N/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":"2026-05-28T16:50:45Z","links":{"resolver":"https://pith.science/pith/E75OD2V7CWWXNX4XRBEALILZ2N","bundle":"https://pith.science/pith/E75OD2V7CWWXNX4XRBEALILZ2N/bundle.json","state":"https://pith.science/pith/E75OD2V7CWWXNX4XRBEALILZ2N/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E75OD2V7CWWXNX4XRBEALILZ2N/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:E75OD2V7CWWXNX4XRBEALILZ2N","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":"576b914b576ad30b2cdaf991f4c82fffe7a884b611c0f6567f7f53d0bd8f05ad","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-09-14T23:26:31Z","title_canon_sha256":"f43f75ac30c2bea0ad33a9be5c237e2f6c7925e571ca2307915dbde9c8c8f731"},"schema_version":"1.0","source":{"id":"1409.4119","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1409.4119","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"arxiv_version","alias_value":"1409.4119v1","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.4119","created_at":"2026-05-18T02:42:53Z"},{"alias_kind":"pith_short_12","alias_value":"E75OD2V7CWWX","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_16","alias_value":"E75OD2V7CWWXNX4X","created_at":"2026-05-18T12:28:25Z"},{"alias_kind":"pith_short_8","alias_value":"E75OD2V7","created_at":"2026-05-18T12:28:25Z"}],"graph_snapshots":[{"event_id":"sha256:649537e83568c20603dc06c8bfa97f8a4269ca5c4f7123d9d26ebe5228b195bb","target":"graph","created_at":"2026-05-18T02:42:53Z","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":"Selecting customers for demand response programs is challenging and existing methodologies are hard to scale and poor in performance. The existing methods were limited by lack of temporal consumption information at the individual customer level. We propose a scalable methodology for demand response targeting utilizing novel data available from smart meters. The approach relies on formulating the problem as a stochastic integer program involving predicted customer responses. A novel approximation is developed algorithm so it can scale to problems involving millions of customers. The methodology","authors_text":"Jungsuk Kwac, Ram Rajagopal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-09-14T23:26:31Z","title":"Targeting Customers for Demand Response Based on Big Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.4119","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":"sha256:59789e4e8e37b9536a83a89818ccfee661696d1721347a1b16b61e4672d9ccaa","target":"record","created_at":"2026-05-18T02:42:53Z","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":"576b914b576ad30b2cdaf991f4c82fffe7a884b611c0f6567f7f53d0bd8f05ad","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2014-09-14T23:26:31Z","title_canon_sha256":"f43f75ac30c2bea0ad33a9be5c237e2f6c7925e571ca2307915dbde9c8c8f731"},"schema_version":"1.0","source":{"id":"1409.4119","kind":"arxiv","version":1}},"canonical_sha256":"27fae1eabf15ad76df97884805a179d347876499e09206141796c405bffffcd1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27fae1eabf15ad76df97884805a179d347876499e09206141796c405bffffcd1","first_computed_at":"2026-05-18T02:42:53.009755Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:42:53.009755Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XlGJZ8H7s7TJQtUqjS/A7rliv1iHzYlrJxaB2mCt9d442y/MeBXMRD+Ki/8moYnlne7BPp/9DdiCQoF3K48uBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:42:53.010156Z","signed_message":"canonical_sha256_bytes"},"source_id":"1409.4119","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59789e4e8e37b9536a83a89818ccfee661696d1721347a1b16b61e4672d9ccaa","sha256:649537e83568c20603dc06c8bfa97f8a4269ca5c4f7123d9d26ebe5228b195bb"],"state_sha256":"9717d127e948fe46217866c36947ded34e038d44ec215352ee452665c9b27718"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iCtuBH7SrpO0vIYcdQuomWJWyP0A3yGxB24Z7aVGodb24+vDr1pOin9BHWodN1dKA2BYTcZSY3FJhIYcj+oHCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T16:50:45.187101Z","bundle_sha256":"783c67caa37432abf1bbbdb6eecba76fbc949220a9bb12fde3f61aa162d4da85"}}