{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:237PYKM3S6747ZYS4BO23Z7MP6","short_pith_number":"pith:237PYKM3","canonical_record":{"source":{"id":"2310.02939","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.GA","submitted_at":"2023-10-04T16:19:48Z","cross_cats_sorted":[],"title_canon_sha256":"f36f6447b2f3941bf4d459e48c2c5f9eafbc6abc61d5dfc7ccbed3e4f31f152a","abstract_canon_sha256":"326be0f2a4a0acded5c44b98252f1eac3fb40d5033a732b89e2057cda2ee7394"},"schema_version":"1.0"},"canonical_sha256":"d6fefc299b97bfcfe712e05dade7ec7fbd88f01d4a451c2e340ffa46d1efc97b","source":{"kind":"arxiv","id":"2310.02939","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02939","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02939v1","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02939","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_12","alias_value":"237PYKM3S674","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_16","alias_value":"237PYKM3S6747ZYS","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_8","alias_value":"237PYKM3","created_at":"2026-07-05T06:57:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:237PYKM3S6747ZYS4BO23Z7MP6","target":"record","payload":{"canonical_record":{"source":{"id":"2310.02939","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.GA","submitted_at":"2023-10-04T16:19:48Z","cross_cats_sorted":[],"title_canon_sha256":"f36f6447b2f3941bf4d459e48c2c5f9eafbc6abc61d5dfc7ccbed3e4f31f152a","abstract_canon_sha256":"326be0f2a4a0acded5c44b98252f1eac3fb40d5033a732b89e2057cda2ee7394"},"schema_version":"1.0"},"canonical_sha256":"d6fefc299b97bfcfe712e05dade7ec7fbd88f01d4a451c2e340ffa46d1efc97b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:57:15.672566Z","signature_b64":"75VI+VnVZJBlVbqqpgBz7/VuKrnlMWFHeVlT+Pbr/fA+0+3KuiC3YI/VcUIb49knW84d7rVgqxujrby1zDuDCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6fefc299b97bfcfe712e05dade7ec7fbd88f01d4a451c2e340ffa46d1efc97b","last_reissued_at":"2026-07-05T06:57:15.672073Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:57:15.672073Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.02939","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":"2026-07-05T06:57:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J0J01URqXSvRqb87ranG9ylRbqnB3TGibL5hvPeLI91gOuPKGvjqB71nv903nfzGS87ZyRVhyofhJLIhzyIDCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:37:34.908926Z"},"content_sha256":"99e3ce1a11d4264f215b8cc62678bf404d95efa62957797c2d97ed81e8252e35","schema_version":"1.0","event_id":"sha256:99e3ce1a11d4264f215b8cc62678bf404d95efa62957797c2d97ed81e8252e35"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:237PYKM3S6747ZYS4BO23Z7MP6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Identifying physical structures in our Galaxy with Gaussian Mixture Models: An unsupervised machine learning technique","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.GA","authors_text":"A. G. G. M. Tielens, C. Guevara, C. Pabst, F. Falasca, J. Stutzki, L. Bonne, M. Justen, M. Tiwari, M. Wolfire, M. W. Pound, N. Schneider, R. Higgins, R. Karim, R. Kievit, R. Simon, S. Kabanovic, \\\"U. Kavak","submitted_at":"2023-10-04T16:19:48Z","abstract_excerpt":"We explore the potential of the Gaussian Mixture Model (GMM), an unsupervised machine learning method, to identify coherent physical structures in the ISM. The implementation we present can be used on any kind of spatially and spectrally resolved data set. We provide a step-by-step guide to use these models on different sources and data sets. Following the guide, we run the models on NGC 1977, RCW 120 and RCW 49 using the [CII] 158 $\\mu$m mapping observations from the SOFIA telescope. We find that the models identified 6, 4 and 5 velocity coherent physical structures in NGC 1977, RCW 120 and R"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02939","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/2310.02939/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":"2026-07-05T06:57:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"thMFNRPNRMVz3Xcz4IN1uKwIs2IWcH5rHHLkS7hsJtnPb9VuU4dxo4rnsTe121Xta6u9qsA32lXWObCPJhK1CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:37:34.909307Z"},"content_sha256":"c2c65e2bcc224f65a89b0fa6ab742f521bb3223347084e29c4e474c850fee039","schema_version":"1.0","event_id":"sha256:c2c65e2bcc224f65a89b0fa6ab742f521bb3223347084e29c4e474c850fee039"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/237PYKM3S6747ZYS4BO23Z7MP6/bundle.json","state_url":"https://pith.science/pith/237PYKM3S6747ZYS4BO23Z7MP6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/237PYKM3S6747ZYS4BO23Z7MP6/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":"2026-07-07T13:37:34Z","links":{"resolver":"https://pith.science/pith/237PYKM3S6747ZYS4BO23Z7MP6","bundle":"https://pith.science/pith/237PYKM3S6747ZYS4BO23Z7MP6/bundle.json","state":"https://pith.science/pith/237PYKM3S6747ZYS4BO23Z7MP6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/237PYKM3S6747ZYS4BO23Z7MP6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:237PYKM3S6747ZYS4BO23Z7MP6","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":"326be0f2a4a0acded5c44b98252f1eac3fb40d5033a732b89e2057cda2ee7394","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.GA","submitted_at":"2023-10-04T16:19:48Z","title_canon_sha256":"f36f6447b2f3941bf4d459e48c2c5f9eafbc6abc61d5dfc7ccbed3e4f31f152a"},"schema_version":"1.0","source":{"id":"2310.02939","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02939","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02939v1","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02939","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_12","alias_value":"237PYKM3S674","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_16","alias_value":"237PYKM3S6747ZYS","created_at":"2026-07-05T06:57:15Z"},{"alias_kind":"pith_short_8","alias_value":"237PYKM3","created_at":"2026-07-05T06:57:15Z"}],"graph_snapshots":[{"event_id":"sha256:c2c65e2bcc224f65a89b0fa6ab742f521bb3223347084e29c4e474c850fee039","target":"graph","created_at":"2026-07-05T06:57:15Z","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/2310.02939/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We explore the potential of the Gaussian Mixture Model (GMM), an unsupervised machine learning method, to identify coherent physical structures in the ISM. The implementation we present can be used on any kind of spatially and spectrally resolved data set. We provide a step-by-step guide to use these models on different sources and data sets. Following the guide, we run the models on NGC 1977, RCW 120 and RCW 49 using the [CII] 158 $\\mu$m mapping observations from the SOFIA telescope. We find that the models identified 6, 4 and 5 velocity coherent physical structures in NGC 1977, RCW 120 and R","authors_text":"A. G. G. M. Tielens, C. Guevara, C. Pabst, F. Falasca, J. Stutzki, L. Bonne, M. Justen, M. Tiwari, M. Wolfire, M. W. Pound, N. Schneider, R. Higgins, R. Karim, R. Kievit, R. Simon, S. Kabanovic, \\\"U. Kavak","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.GA","submitted_at":"2023-10-04T16:19:48Z","title":"Identifying physical structures in our Galaxy with Gaussian Mixture Models: An unsupervised machine learning technique"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02939","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":"sha256:99e3ce1a11d4264f215b8cc62678bf404d95efa62957797c2d97ed81e8252e35","target":"record","created_at":"2026-07-05T06:57:15Z","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":"326be0f2a4a0acded5c44b98252f1eac3fb40d5033a732b89e2057cda2ee7394","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.GA","submitted_at":"2023-10-04T16:19:48Z","title_canon_sha256":"f36f6447b2f3941bf4d459e48c2c5f9eafbc6abc61d5dfc7ccbed3e4f31f152a"},"schema_version":"1.0","source":{"id":"2310.02939","kind":"arxiv","version":1}},"canonical_sha256":"d6fefc299b97bfcfe712e05dade7ec7fbd88f01d4a451c2e340ffa46d1efc97b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6fefc299b97bfcfe712e05dade7ec7fbd88f01d4a451c2e340ffa46d1efc97b","first_computed_at":"2026-07-05T06:57:15.672073Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:57:15.672073Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"75VI+VnVZJBlVbqqpgBz7/VuKrnlMWFHeVlT+Pbr/fA+0+3KuiC3YI/VcUIb49knW84d7rVgqxujrby1zDuDCA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:57:15.672566Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.02939","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:99e3ce1a11d4264f215b8cc62678bf404d95efa62957797c2d97ed81e8252e35","sha256:c2c65e2bcc224f65a89b0fa6ab742f521bb3223347084e29c4e474c850fee039"],"state_sha256":"67840016e6a1f19223c83bed835f46f71063b97e0f309b344cb73d6b474da4d6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lh23639C3ukeohT4Ov4c+MJi3c67mLcWNpx/MAkInkGVN8cSNxLla+wT352VkC/McHlQBy72adRysg3Rw9CpBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T13:37:34.911181Z","bundle_sha256":"ed23e68f55d55c6d2ad7ac9f442b6b675a474b910e6a3d29787336de8daae81b"}}