{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7YBNQM3QUK6TTP4W5EATY5UCAT","short_pith_number":"pith:7YBNQM3Q","canonical_record":{"source":{"id":"2102.10326","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-02-20T12:28:39Z","cross_cats_sorted":["astro-ph.IM","cs.LG"],"title_canon_sha256":"eb8de7111649b8ff2c2d136501e21e2e78504471477d9ccfc9d0092e2d91cab0","abstract_canon_sha256":"d874b08fc5c09089e79a1a7c46defc01871f61b7230cdd126cb52cfebbb6d35f"},"schema_version":"1.0"},"canonical_sha256":"fe02d83370a2bd39bf96e9013c768204fb3d8320afac4511ffc882a39b339b04","source":{"kind":"arxiv","id":"2102.10326","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.10326","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"arxiv_version","alias_value":"2102.10326v2","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.10326","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_12","alias_value":"7YBNQM3QUK6T","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_16","alias_value":"7YBNQM3QUK6TTP4W","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_8","alias_value":"7YBNQM3Q","created_at":"2026-07-05T03:11:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7YBNQM3QUK6TTP4W5EATY5UCAT","target":"record","payload":{"canonical_record":{"source":{"id":"2102.10326","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-02-20T12:28:39Z","cross_cats_sorted":["astro-ph.IM","cs.LG"],"title_canon_sha256":"eb8de7111649b8ff2c2d136501e21e2e78504471477d9ccfc9d0092e2d91cab0","abstract_canon_sha256":"d874b08fc5c09089e79a1a7c46defc01871f61b7230cdd126cb52cfebbb6d35f"},"schema_version":"1.0"},"canonical_sha256":"fe02d83370a2bd39bf96e9013c768204fb3d8320afac4511ffc882a39b339b04","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:11:59.619482Z","signature_b64":"tPcyB7k1IESakEwZKFLwD+9cenIF9zc3k/yItVHtkmjlHipyxV50AyI199QD/VFf8wssog5zg2GtA/mI7Da4BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe02d83370a2bd39bf96e9013c768204fb3d8320afac4511ffc882a39b339b04","last_reissued_at":"2026-07-05T03:11:59.618979Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:11:59.618979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2102.10326","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:11:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bpwcj+pLnc2FzETHkNxA330NKM4mVkgv647iIBHwGCEkrsIP35g7QVM4Wrhpf8fc2Q8sKS9yzrQil5pYyauiBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T20:31:01.244263Z"},"content_sha256":"5d5353d7b7d200bd10f6f13d2f7fb082b320e16ba3a78152765abaf717e10503","schema_version":"1.0","event_id":"sha256:5d5353d7b7d200bd10f6f13d2f7fb082b320e16ba3a78152765abaf717e10503"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7YBNQM3QUK6TTP4W5EATY5UCAT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automated identification of transiting exoplanet candidates in NASA Transiting Exoplanets Survey Satellite (TESS) data with machine learning methods","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG"],"primary_cat":"astro-ph.EP","authors_text":"Adi Shliselberg, Amir Averbuch, Aron Rissman, David Segev, Idan Benaun, Leon Ofman","submitted_at":"2021-02-20T12:28:39Z","abstract_excerpt":"A novel artificial intelligence (AI) technique that uses machine learning (ML) methodologies combines several algorithms, which were developed by ThetaRay, Inc., is applied to NASA's Transiting Exoplanets Survey Satellite (TESS) dataset to identify exoplanetary candidates. The AI/ML ThetaRay system is trained initially with Kepler exoplanetary data and validated with confirmed exoplanets before its application to TESS data. Existing and new features of the data, based on various observational parameters, are constructed and used in the AI/ML analysis by employing semi-supervised and unsupervis"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.10326","kind":"arxiv","version":2},"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/2102.10326/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":"2026-07-05T03:11:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VfxyJhiCae6oyPc6pnmrChKyQdrjUtWakpKw2fMsU02AL0ewxAu71ZI23KMcuwCaSbQF/simPrK3n/urA2qYAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T20:31:01.244786Z"},"content_sha256":"e4149ebf5f986e3690e2e441998997c1ef0474ff92321bde8db990086e505c74","schema_version":"1.0","event_id":"sha256:e4149ebf5f986e3690e2e441998997c1ef0474ff92321bde8db990086e505c74"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/bundle.json","state_url":"https://pith.science/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/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":"2026-08-06T20:31:01Z","links":{"resolver":"https://pith.science/pith/7YBNQM3QUK6TTP4W5EATY5UCAT","bundle":"https://pith.science/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/bundle.json","state":"https://pith.science/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7YBNQM3QUK6TTP4W5EATY5UCAT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7YBNQM3QUK6TTP4W5EATY5UCAT","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":"d874b08fc5c09089e79a1a7c46defc01871f61b7230cdd126cb52cfebbb6d35f","cross_cats_sorted":["astro-ph.IM","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-02-20T12:28:39Z","title_canon_sha256":"eb8de7111649b8ff2c2d136501e21e2e78504471477d9ccfc9d0092e2d91cab0"},"schema_version":"1.0","source":{"id":"2102.10326","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.10326","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"arxiv_version","alias_value":"2102.10326v2","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.10326","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_12","alias_value":"7YBNQM3QUK6T","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_16","alias_value":"7YBNQM3QUK6TTP4W","created_at":"2026-07-05T03:11:59Z"},{"alias_kind":"pith_short_8","alias_value":"7YBNQM3Q","created_at":"2026-07-05T03:11:59Z"}],"graph_snapshots":[{"event_id":"sha256:e4149ebf5f986e3690e2e441998997c1ef0474ff92321bde8db990086e505c74","target":"graph","created_at":"2026-07-05T03:11:59Z","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/2102.10326/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A novel artificial intelligence (AI) technique that uses machine learning (ML) methodologies combines several algorithms, which were developed by ThetaRay, Inc., is applied to NASA's Transiting Exoplanets Survey Satellite (TESS) dataset to identify exoplanetary candidates. The AI/ML ThetaRay system is trained initially with Kepler exoplanetary data and validated with confirmed exoplanets before its application to TESS data. Existing and new features of the data, based on various observational parameters, are constructed and used in the AI/ML analysis by employing semi-supervised and unsupervis","authors_text":"Adi Shliselberg, Amir Averbuch, Aron Rissman, David Segev, Idan Benaun, Leon Ofman","cross_cats":["astro-ph.IM","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-02-20T12:28:39Z","title":"Automated identification of transiting exoplanet candidates in NASA Transiting Exoplanets Survey Satellite (TESS) data with machine learning methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.10326","kind":"arxiv","version":2},"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":"sha256:5d5353d7b7d200bd10f6f13d2f7fb082b320e16ba3a78152765abaf717e10503","target":"record","created_at":"2026-07-05T03:11:59Z","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":"d874b08fc5c09089e79a1a7c46defc01871f61b7230cdd126cb52cfebbb6d35f","cross_cats_sorted":["astro-ph.IM","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.EP","submitted_at":"2021-02-20T12:28:39Z","title_canon_sha256":"eb8de7111649b8ff2c2d136501e21e2e78504471477d9ccfc9d0092e2d91cab0"},"schema_version":"1.0","source":{"id":"2102.10326","kind":"arxiv","version":2}},"canonical_sha256":"fe02d83370a2bd39bf96e9013c768204fb3d8320afac4511ffc882a39b339b04","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe02d83370a2bd39bf96e9013c768204fb3d8320afac4511ffc882a39b339b04","first_computed_at":"2026-07-05T03:11:59.618979Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:11:59.618979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tPcyB7k1IESakEwZKFLwD+9cenIF9zc3k/yItVHtkmjlHipyxV50AyI199QD/VFf8wssog5zg2GtA/mI7Da4BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:11:59.619482Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.10326","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5d5353d7b7d200bd10f6f13d2f7fb082b320e16ba3a78152765abaf717e10503","sha256:e4149ebf5f986e3690e2e441998997c1ef0474ff92321bde8db990086e505c74"],"state_sha256":"da014ee09bff6ff4bf0bc39f336ba49d7f517565baf18a1e19387eb62e74065e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9NaS9Yazf+vtSFSavIAsPMZBrxlAFRHlsVNzvbI8w/wGOpglJJpghRldB1Glr7P9Mp9sHTOxpnxK+7HbE9SWBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T20:31:01.250220Z","bundle_sha256":"d5b42413cc81a4afcd092a4009a2e74b304c310d8b76cb4570c3055cfac225c8"}}