{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2013:ZAFWDTV6E7NAZZLV5MSC7ZEAH5","short_pith_number":"pith:ZAFWDTV6","schema_version":"1.0","canonical_sha256":"c80b61cebe27da0ce575eb242fe4803f7aff3d1d866d3b67c30fb657fbeaa3ee","source":{"kind":"arxiv","id":"1306.0935","version":1},"attestation_state":"computed","paper":{"title":"Quick-MESS: A fast statistical tool for Exoplanet Imaging Surveys","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.EP"],"primary_cat":"astro-ph.IM","authors_text":"Ernst J.W. de Mooij, Mariangela Bonavita, Ray Jayawardhana","submitted_at":"2013-06-04T22:13:46Z","abstract_excerpt":"Several tools have been developed in the past few years for the statistical analysis of the exoplanet search surveys, mostly using a combination of Monte-Carlo simulations or a Bayesian approach.Here we present the Quick-MESS, a grid-based, non-Monte Carlo tool aimed to perform statistical analyses on results from and help with the planning of direct imaging surveys. Quick-MESS uses the (expected) contrast curves for direct imaging surveys to assess for each target the probability that a planet of a given mass and semi-major axis can be detected. By using a grid-based approach Quick-MESS is ty"},"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":"1306.0935","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2013-06-04T22:13:46Z","cross_cats_sorted":["astro-ph.EP"],"title_canon_sha256":"6c0652a5fa35ec0ab0bbdbb74bc4326aa122b50405844824f3da6767b979e641","abstract_canon_sha256":"99888ea655fc33b9052a90a54d34303a8c618a352423bf02a682020b8d1f9275"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:49:32.842852Z","signature_b64":"yk2N5RFQWfDGiEO2maLi7auDaNheBidi+s2n/MS7ZpJN2W5A1i1D6Oz/bUbpn+tKvrjvD9WhU99M2LOleZpcCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c80b61cebe27da0ce575eb242fe4803f7aff3d1d866d3b67c30fb657fbeaa3ee","last_reissued_at":"2026-05-18T01:49:32.842453Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:49:32.842453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quick-MESS: A fast statistical tool for Exoplanet Imaging Surveys","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.EP"],"primary_cat":"astro-ph.IM","authors_text":"Ernst J.W. de Mooij, Mariangela Bonavita, Ray Jayawardhana","submitted_at":"2013-06-04T22:13:46Z","abstract_excerpt":"Several tools have been developed in the past few years for the statistical analysis of the exoplanet search surveys, mostly using a combination of Monte-Carlo simulations or a Bayesian approach.Here we present the Quick-MESS, a grid-based, non-Monte Carlo tool aimed to perform statistical analyses on results from and help with the planning of direct imaging surveys. Quick-MESS uses the (expected) contrast curves for direct imaging surveys to assess for each target the probability that a planet of a given mass and semi-major axis can be detected. By using a grid-based approach Quick-MESS is ty"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1306.0935","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1306.0935","created_at":"2026-05-18T01:49:32.842516+00:00"},{"alias_kind":"arxiv_version","alias_value":"1306.0935v1","created_at":"2026-05-18T01:49:32.842516+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1306.0935","created_at":"2026-05-18T01:49:32.842516+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZAFWDTV6E7NA","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZAFWDTV6E7NAZZLV","created_at":"2026-05-18T12:28:09.283467+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZAFWDTV6","created_at":"2026-05-18T12:28:09.283467+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/ZAFWDTV6E7NAZZLV5MSC7ZEAH5","json":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5.json","graph_json":"https://pith.science/api/pith-number/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/graph.json","events_json":"https://pith.science/api/pith-number/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/events.json","paper":"https://pith.science/paper/ZAFWDTV6"},"agent_actions":{"view_html":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5","download_json":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5.json","view_paper":"https://pith.science/paper/ZAFWDTV6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1306.0935&json=true","fetch_graph":"https://pith.science/api/pith-number/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/graph.json","fetch_events":"https://pith.science/api/pith-number/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/action/storage_attestation","attest_author":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/action/author_attestation","sign_citation":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/action/citation_signature","submit_replication":"https://pith.science/pith/ZAFWDTV6E7NAZZLV5MSC7ZEAH5/action/replication_record"}},"created_at":"2026-05-18T01:49:32.842516+00:00","updated_at":"2026-05-18T01:49:32.842516+00:00"}