{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PFJATAUA7BJNUH34JJGIODNQ3D","short_pith_number":"pith:PFJATAUA","canonical_record":{"source":{"id":"1907.10176","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-07-23T23:21:30Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"2cb694a658e6178559ca1368f2d1e9fe9f0e9982c56cfbe20cf034b94d61758d","abstract_canon_sha256":"6f47acd15be102b6a0d37e091c1da092d4d7d77e53caf6e0e45aa6e2c295dbe5"},"schema_version":"1.0"},"canonical_sha256":"7952098280f852da1f7c4a4c870db0d8df70a5c5e878c3447a8a49ff658c2609","source":{"kind":"arxiv","id":"1907.10176","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10176","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10176v1","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10176","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"pith_short_12","alias_value":"PFJATAUA7BJN","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PFJATAUA7BJNUH34","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PFJATAUA","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PFJATAUA7BJNUH34JJGIODNQ3D","target":"record","payload":{"canonical_record":{"source":{"id":"1907.10176","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-07-23T23:21:30Z","cross_cats_sorted":["stat.ME","stat.TH"],"title_canon_sha256":"2cb694a658e6178559ca1368f2d1e9fe9f0e9982c56cfbe20cf034b94d61758d","abstract_canon_sha256":"6f47acd15be102b6a0d37e091c1da092d4d7d77e53caf6e0e45aa6e2c295dbe5"},"schema_version":"1.0"},"canonical_sha256":"7952098280f852da1f7c4a4c870db0d8df70a5c5e878c3447a8a49ff658c2609","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:38.768715Z","signature_b64":"0xhnGJ2pVWUQD8oBtbNvsfM2yiwFiF3+tdq/246xG3wN2eVVh2Jz/3LpJIj4vqvgi5jL+2wLSi69tRxLE2QlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7952098280f852da1f7c4a4c870db0d8df70a5c5e878c3447a8a49ff658c2609","last_reissued_at":"2026-05-17T23:39:38.768085Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:38.768085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.10176","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":"2026-05-17T23:39:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yWSMD8ws+KE+IpdpXOBpHfdfo4/h4hf3fWxJqIGi4YZETCjXjXGWHcepmfjTGY6y+sVMwh1Oq4B8Ak9wGALQBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:06:22.434285Z"},"content_sha256":"1d7e9a5cef12f90bb6eef84c7b7b8ad7f2adc870cad728b00aa7c8f35c93e214","schema_version":"1.0","event_id":"sha256:1d7e9a5cef12f90bb6eef84c7b7b8ad7f2adc870cad728b00aa7c8f35c93e214"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PFJATAUA7BJNUH34JJGIODNQ3D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Graph inference with clustering and false discovery rate control","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME","stat.TH"],"primary_cat":"math.ST","authors_text":"Etienne Roquain, Fanny Villers, Tabea Rebafka","submitted_at":"2019-07-23T23:21:30Z","abstract_excerpt":"In this paper, a noisy version of the stochastic block model (NSBM) is introduced and we investigate the three following statistical inferences in this model: estimation of the model parameters, clustering of the nodes and identification of the underlying graph. While the two first inferences are done by using a variational expectation-maximization (VEM) algorithm, the graph inference is done by controlling the false discovery rate (FDR), that is, the average proportion of errors among the edges declared significant, and by maximizing the true discovery rate (TDR), that is, the average proport"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10176","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":"2026-05-17T23:39:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tes2uVXR9Z9+XojbfmSDIXav3wbGAnp2FVfkQnPwr/xlrtLqmXQS0VitIEcYk46CtMQCFVWYOi+M3V/fTRoEBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T08:06:22.434676Z"},"content_sha256":"2d56ade08a30b211f543d454d35e88231b5b3136991acb8157d097969ccce2b3","schema_version":"1.0","event_id":"sha256:2d56ade08a30b211f543d454d35e88231b5b3136991acb8157d097969ccce2b3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PFJATAUA7BJNUH34JJGIODNQ3D/bundle.json","state_url":"https://pith.science/pith/PFJATAUA7BJNUH34JJGIODNQ3D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PFJATAUA7BJNUH34JJGIODNQ3D/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":"2026-05-31T08:06:22Z","links":{"resolver":"https://pith.science/pith/PFJATAUA7BJNUH34JJGIODNQ3D","bundle":"https://pith.science/pith/PFJATAUA7BJNUH34JJGIODNQ3D/bundle.json","state":"https://pith.science/pith/PFJATAUA7BJNUH34JJGIODNQ3D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PFJATAUA7BJNUH34JJGIODNQ3D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PFJATAUA7BJNUH34JJGIODNQ3D","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":"6f47acd15be102b6a0d37e091c1da092d4d7d77e53caf6e0e45aa6e2c295dbe5","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-07-23T23:21:30Z","title_canon_sha256":"2cb694a658e6178559ca1368f2d1e9fe9f0e9982c56cfbe20cf034b94d61758d"},"schema_version":"1.0","source":{"id":"1907.10176","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10176","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10176v1","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10176","created_at":"2026-05-17T23:39:38Z"},{"alias_kind":"pith_short_12","alias_value":"PFJATAUA7BJN","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PFJATAUA7BJNUH34","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PFJATAUA","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:2d56ade08a30b211f543d454d35e88231b5b3136991acb8157d097969ccce2b3","target":"graph","created_at":"2026-05-17T23:39:38Z","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 this paper, a noisy version of the stochastic block model (NSBM) is introduced and we investigate the three following statistical inferences in this model: estimation of the model parameters, clustering of the nodes and identification of the underlying graph. While the two first inferences are done by using a variational expectation-maximization (VEM) algorithm, the graph inference is done by controlling the false discovery rate (FDR), that is, the average proportion of errors among the edges declared significant, and by maximizing the true discovery rate (TDR), that is, the average proport","authors_text":"Etienne Roquain, Fanny Villers, Tabea Rebafka","cross_cats":["stat.ME","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-07-23T23:21:30Z","title":"Graph inference with clustering and false discovery rate control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10176","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":"sha256:1d7e9a5cef12f90bb6eef84c7b7b8ad7f2adc870cad728b00aa7c8f35c93e214","target":"record","created_at":"2026-05-17T23:39:38Z","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":"6f47acd15be102b6a0d37e091c1da092d4d7d77e53caf6e0e45aa6e2c295dbe5","cross_cats_sorted":["stat.ME","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2019-07-23T23:21:30Z","title_canon_sha256":"2cb694a658e6178559ca1368f2d1e9fe9f0e9982c56cfbe20cf034b94d61758d"},"schema_version":"1.0","source":{"id":"1907.10176","kind":"arxiv","version":1}},"canonical_sha256":"7952098280f852da1f7c4a4c870db0d8df70a5c5e878c3447a8a49ff658c2609","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7952098280f852da1f7c4a4c870db0d8df70a5c5e878c3447a8a49ff658c2609","first_computed_at":"2026-05-17T23:39:38.768085Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:38.768085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0xhnGJ2pVWUQD8oBtbNvsfM2yiwFiF3+tdq/246xG3wN2eVVh2Jz/3LpJIj4vqvgi5jL+2wLSi69tRxLE2QlDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:38.768715Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.10176","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1d7e9a5cef12f90bb6eef84c7b7b8ad7f2adc870cad728b00aa7c8f35c93e214","sha256:2d56ade08a30b211f543d454d35e88231b5b3136991acb8157d097969ccce2b3"],"state_sha256":"9643176b3e89582a088bcc2a00e66565a08ac17cbd5b32c0800cf3ee9276559d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pz+GrFZG3bHBtN+BAfvqPSqNBQARVhKEyQqlq4fSjeMmGqLFSiGDvabRCrH0UUD2TsknaGVcX+gq6cjMqLyDDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T08:06:22.437095Z","bundle_sha256":"ddcba5f8fc0d33d2c07df6b5fea88db6c50f58f844fedf3b075a7a64e3cedfa5"}}