{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:LM3BJT32DYER7DEXXMY6ETSDNU","short_pith_number":"pith:LM3BJT32","schema_version":"1.0","canonical_sha256":"5b3614cf7a1e091f8c97bb31e24e436d3319f1e27920334af889048b0522d91b","source":{"kind":"arxiv","id":"2305.09294","version":1},"attestation_state":"computed","paper":{"title":"S-type stars from LAMOST DR10: classification of intrinsic and extrinsic stars","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.GA"],"primary_cat":"astro-ph.SR","authors_text":"A-Li Luo, Jing Chen, Shuo Li, Xiao-Xiao Ma, Yin-Bi Li","submitted_at":"2023-05-16T09:03:37Z","abstract_excerpt":"In this paper, we found 2939 S-type stars from LAMOST Data Release 10 using two machine-learning methods, and 2306 of them were reported for the first time. The main purpose of this work is to study how to divide S-type stars into intrinsic and extrinsic stars with photometric data and LAMOST spectra. Using infrared photometric data, we adopted two methods to distinguish S-type stars, i.e., XGBoost algorithm and color-color diagrams. We trained XGBoost model with 15 input features consisting of colors and absolute magnitudes of Two Micron All Sky Survey (2MASS), AllWISE, AKARI, and IRAS, and f"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.09294","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2023-05-16T09:03:37Z","cross_cats_sorted":["astro-ph.GA"],"title_canon_sha256":"b7a39ac0db9c7ac9a4c52d779e7c57b55b7b0c3e04a5cada6764c0f19ebf4987","abstract_canon_sha256":"44801f977e0cdcb83cc826f145665815d8fce5a60e8e6defbcdee721bf710532"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:27:23.895435Z","signature_b64":"oGMYC0e27xl826mUiAwikdFeqbD6poqoJ4T/fly2oLLbNee9NnxltHDyDhYA3XJl30fLXeZ+DcwwNX2Uv/JIAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b3614cf7a1e091f8c97bb31e24e436d3319f1e27920334af889048b0522d91b","last_reissued_at":"2026-07-05T06:27:23.895035Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:27:23.895035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"S-type stars from LAMOST DR10: classification of intrinsic and extrinsic stars","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.GA"],"primary_cat":"astro-ph.SR","authors_text":"A-Li Luo, Jing Chen, Shuo Li, Xiao-Xiao Ma, Yin-Bi Li","submitted_at":"2023-05-16T09:03:37Z","abstract_excerpt":"In this paper, we found 2939 S-type stars from LAMOST Data Release 10 using two machine-learning methods, and 2306 of them were reported for the first time. The main purpose of this work is to study how to divide S-type stars into intrinsic and extrinsic stars with photometric data and LAMOST spectra. Using infrared photometric data, we adopted two methods to distinguish S-type stars, i.e., XGBoost algorithm and color-color diagrams. We trained XGBoost model with 15 input features consisting of colors and absolute magnitudes of Two Micron All Sky Survey (2MASS), AllWISE, AKARI, and IRAS, and f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.09294","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/2305.09294/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.09294","created_at":"2026-07-05T06:27:23.895090+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.09294v1","created_at":"2026-07-05T06:27:23.895090+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.09294","created_at":"2026-07-05T06:27:23.895090+00:00"},{"alias_kind":"pith_short_12","alias_value":"LM3BJT32DYER","created_at":"2026-07-05T06:27:23.895090+00:00"},{"alias_kind":"pith_short_16","alias_value":"LM3BJT32DYER7DEX","created_at":"2026-07-05T06:27:23.895090+00:00"},{"alias_kind":"pith_short_8","alias_value":"LM3BJT32","created_at":"2026-07-05T06:27:23.895090+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU","json":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU.json","graph_json":"https://pith.science/api/pith-number/LM3BJT32DYER7DEXXMY6ETSDNU/graph.json","events_json":"https://pith.science/api/pith-number/LM3BJT32DYER7DEXXMY6ETSDNU/events.json","paper":"https://pith.science/paper/LM3BJT32"},"agent_actions":{"view_html":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU","download_json":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU.json","view_paper":"https://pith.science/paper/LM3BJT32","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.09294&json=true","fetch_graph":"https://pith.science/api/pith-number/LM3BJT32DYER7DEXXMY6ETSDNU/graph.json","fetch_events":"https://pith.science/api/pith-number/LM3BJT32DYER7DEXXMY6ETSDNU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU/action/storage_attestation","attest_author":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU/action/author_attestation","sign_citation":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU/action/citation_signature","submit_replication":"https://pith.science/pith/LM3BJT32DYER7DEXXMY6ETSDNU/action/replication_record"}},"created_at":"2026-07-05T06:27:23.895090+00:00","updated_at":"2026-07-05T06:27:23.895090+00:00"}