{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IZ3OYGWMV676UMSNVDZTXW53ZA","short_pith_number":"pith:IZ3OYGWM","canonical_record":{"source":{"id":"2508.04982","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-08-07T02:28:21Z","cross_cats_sorted":["astro-ph.IM","cs.LG","physics.data-an"],"title_canon_sha256":"4fb96af804d7a0f5283b711a7b2327a5172a3f5febe4132eccc01984d6c81da0","abstract_canon_sha256":"77ff5fbba9c43b584ad692d3b0d2952b91109a1ee89b35621f8c9cbc93447d2b"},"schema_version":"1.0"},"canonical_sha256":"4676ec1accafbfea324da8f33bdbbbc808e07372925758c261f165ca8b2f9c73","source":{"kind":"arxiv","id":"2508.04982","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04982","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04982v1","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04982","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_12","alias_value":"IZ3OYGWMV676","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_16","alias_value":"IZ3OYGWMV676UMSN","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_8","alias_value":"IZ3OYGWM","created_at":"2026-07-05T11:50:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IZ3OYGWMV676UMSNVDZTXW53ZA","target":"record","payload":{"canonical_record":{"source":{"id":"2508.04982","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-08-07T02:28:21Z","cross_cats_sorted":["astro-ph.IM","cs.LG","physics.data-an"],"title_canon_sha256":"4fb96af804d7a0f5283b711a7b2327a5172a3f5febe4132eccc01984d6c81da0","abstract_canon_sha256":"77ff5fbba9c43b584ad692d3b0d2952b91109a1ee89b35621f8c9cbc93447d2b"},"schema_version":"1.0"},"canonical_sha256":"4676ec1accafbfea324da8f33bdbbbc808e07372925758c261f165ca8b2f9c73","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:05.111103Z","signature_b64":"LxofbIdpkmT3b6dB/4rim8WnfO79522+NP/TGma9umkHIL8iPQACQSmz4uH3AyynVDhiakBYTGS/NTiNZJSBBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4676ec1accafbfea324da8f33bdbbbc808e07372925758c261f165ca8b2f9c73","last_reissued_at":"2026-07-05T11:50:05.110679Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:05.110679Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.04982","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":"2026-07-05T11:50:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hMA+AbTRSn4LzsblD0Xi98lMADNa5OsHJFiCre6Wu9ew3qih28CY9zVqALKTQf/vDc2SbPnwGi50Nj6/u7XcBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:10:21.929958Z"},"content_sha256":"142b6b9f6508dc02b2a43b61b88914e0094a6f8690d0cfac922e9f85d6a9b1e3","schema_version":"1.0","event_id":"sha256:142b6b9f6508dc02b2a43b61b88914e0094a6f8690d0cfac922e9f85d6a9b1e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IZ3OYGWMV676UMSNVDZTXW53ZA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG","physics.data-an"],"primary_cat":"astro-ph.EP","authors_text":"Eyup B. Unlu, Katia Matcheva, Konstantin T. Matchev, Roy T. Forestano","submitted_at":"2025-08-07T02:28:21Z","abstract_excerpt":"Standard Bayesian retrievals for exoplanet atmospheric parameters from transmission spectroscopy, while well understood and widely used, are generally computationally expensive. In the era of the JWST and other upcoming observatories, machine learning approaches have emerged as viable alternatives that are both efficient and robust. In this paper we present a systematic study of several existing machine learning regression techniques and compare their performance for retrieving exoplanet atmospheric parameters from transmission spectra. We benchmark the performance of the different algorithms "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04982","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/2508.04982/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":"2026-07-05T11:50:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g1w2swVNL5cPyjPmuUvoQ4Cw7ApwPf+k0JyAZkQwwR84JEAMTQpVI/W0jLlQ2qLBnqAhM1dX8VekqiZOPqkKBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:10:21.930941Z"},"content_sha256":"dce1d67d5281f7bc4c3d20f8a1d84f05035ebc7c12f024c56cf31fe777830894","schema_version":"1.0","event_id":"sha256:dce1d67d5281f7bc4c3d20f8a1d84f05035ebc7c12f024c56cf31fe777830894"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/bundle.json","state_url":"https://pith.science/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/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":"2026-08-06T12:10:21Z","links":{"resolver":"https://pith.science/pith/IZ3OYGWMV676UMSNVDZTXW53ZA","bundle":"https://pith.science/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/bundle.json","state":"https://pith.science/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IZ3OYGWMV676UMSNVDZTXW53ZA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IZ3OYGWMV676UMSNVDZTXW53ZA","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":"77ff5fbba9c43b584ad692d3b0d2952b91109a1ee89b35621f8c9cbc93447d2b","cross_cats_sorted":["astro-ph.IM","cs.LG","physics.data-an"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-08-07T02:28:21Z","title_canon_sha256":"4fb96af804d7a0f5283b711a7b2327a5172a3f5febe4132eccc01984d6c81da0"},"schema_version":"1.0","source":{"id":"2508.04982","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04982","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04982v1","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04982","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_12","alias_value":"IZ3OYGWMV676","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_16","alias_value":"IZ3OYGWMV676UMSN","created_at":"2026-07-05T11:50:05Z"},{"alias_kind":"pith_short_8","alias_value":"IZ3OYGWM","created_at":"2026-07-05T11:50:05Z"}],"graph_snapshots":[{"event_id":"sha256:dce1d67d5281f7bc4c3d20f8a1d84f05035ebc7c12f024c56cf31fe777830894","target":"graph","created_at":"2026-07-05T11:50:05Z","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/2508.04982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Standard Bayesian retrievals for exoplanet atmospheric parameters from transmission spectroscopy, while well understood and widely used, are generally computationally expensive. In the era of the JWST and other upcoming observatories, machine learning approaches have emerged as viable alternatives that are both efficient and robust. In this paper we present a systematic study of several existing machine learning regression techniques and compare their performance for retrieving exoplanet atmospheric parameters from transmission spectra. We benchmark the performance of the different algorithms ","authors_text":"Eyup B. Unlu, Katia Matcheva, Konstantin T. Matchev, Roy T. Forestano","cross_cats":["astro-ph.IM","cs.LG","physics.data-an"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-08-07T02:28:21Z","title":"Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04982","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":"sha256:142b6b9f6508dc02b2a43b61b88914e0094a6f8690d0cfac922e9f85d6a9b1e3","target":"record","created_at":"2026-07-05T11:50:05Z","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":"77ff5fbba9c43b584ad692d3b0d2952b91109a1ee89b35621f8c9cbc93447d2b","cross_cats_sorted":["astro-ph.IM","cs.LG","physics.data-an"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.EP","submitted_at":"2025-08-07T02:28:21Z","title_canon_sha256":"4fb96af804d7a0f5283b711a7b2327a5172a3f5febe4132eccc01984d6c81da0"},"schema_version":"1.0","source":{"id":"2508.04982","kind":"arxiv","version":1}},"canonical_sha256":"4676ec1accafbfea324da8f33bdbbbc808e07372925758c261f165ca8b2f9c73","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4676ec1accafbfea324da8f33bdbbbc808e07372925758c261f165ca8b2f9c73","first_computed_at":"2026-07-05T11:50:05.110679Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:05.110679Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LxofbIdpkmT3b6dB/4rim8WnfO79522+NP/TGma9umkHIL8iPQACQSmz4uH3AyynVDhiakBYTGS/NTiNZJSBBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:05.111103Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.04982","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:142b6b9f6508dc02b2a43b61b88914e0094a6f8690d0cfac922e9f85d6a9b1e3","sha256:dce1d67d5281f7bc4c3d20f8a1d84f05035ebc7c12f024c56cf31fe777830894"],"state_sha256":"e147e0f56565b6a4d2781907f13ed669130629968bb29f52c8a1a84535e82cd2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k2Zb722FW2o0W5rMENAl4N2aDt2Nba3qFVxOdcHF6/JWuz0C20tDELwQR5twSwbNxsYyLBYajDiWGl2bkKwbCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T12:10:21.937700Z","bundle_sha256":"bc39edd27695e67e999fa2f8ec910d82b7789daad0aeac87b535b5b35919eff3"}}