{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GGEZH2XKRNTBHBXW7GIUZEHSGM","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":"8d729e2c9dcf0de58f6bdbbd29abb7498e1576e690ed7da988160f85f0cb3f65","cross_cats_sorted":["math.ST","stat.AP","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-29T16:17:17Z","title_canon_sha256":"34c35846a25efa7e2b45ee73df7b4a073631f0c5be260f281a2a02efc932d50b"},"schema_version":"1.0","source":{"id":"1711.10937","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.10937","created_at":"2026-05-17T23:44:04Z"},{"alias_kind":"arxiv_version","alias_value":"1711.10937v1","created_at":"2026-05-17T23:44:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.10937","created_at":"2026-05-17T23:44:04Z"},{"alias_kind":"pith_short_12","alias_value":"GGEZH2XKRNTB","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"GGEZH2XKRNTBHBXW","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"GGEZH2XK","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:ba844df294200b73294fe5ae122cc449cf2812b35f15e9c6c58f80f98dabc150","target":"graph","created_at":"2026-05-17T23:44:04Z","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"},"paper":{"abstract_excerpt":"Rainfall ensemble forecasts have to be skillful for both low precipitation and extreme events. We present statistical post-processing methods based on Quantile Regression Forests (QRF) and Gradient Forests (GF) with a parametric extension for heavy-tailed distributions. Our goal is to improve ensemble quality for all types of precipitation events, heavy-tailed included, subject to a good overall performance. Our hybrid proposed methods are applied to daily 51-h forecasts of 6-h accumulated precipitation from 2012 to 2015 over France using the M{\\'e}t{\\'e}o-France ensemble prediction system cal","authors_text":"2, (2) LSCE, 3), (3) ICJ), Anne-Laure Foug\\`eres (3), Maxime Taillardat (1, Olivier Mestre (1) ((1) CNRM, Philippe Naveau (2)","cross_cats":["math.ST","stat.AP","stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-29T16:17:17Z","title":"Forest-based methods and ensemble model output statistics for rainfall ensemble forecasting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.10937","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:ced032c1913ea4b2b26d8d00a3936e03f3637ac476cd8d633dc5b5f3e9ebb218","target":"record","created_at":"2026-05-17T23:44:04Z","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":"8d729e2c9dcf0de58f6bdbbd29abb7498e1576e690ed7da988160f85f0cb3f65","cross_cats_sorted":["math.ST","stat.AP","stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-11-29T16:17:17Z","title_canon_sha256":"34c35846a25efa7e2b45ee73df7b4a073631f0c5be260f281a2a02efc932d50b"},"schema_version":"1.0","source":{"id":"1711.10937","kind":"arxiv","version":1}},"canonical_sha256":"318993eaea8b661386f6f9914c90f23329e83127fafe2c0127e2acad1ddfeb61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"318993eaea8b661386f6f9914c90f23329e83127fafe2c0127e2acad1ddfeb61","first_computed_at":"2026-05-17T23:44:04.807754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:04.807754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EVkEIE4cck8Wh8QUyyRf6b68tJNF4VbUsCACEScDjwVykxUnyO3qStXhJxIjR+4c7g5bpdItMyGV5JWy1H2XBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:04.808154Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.10937","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ced032c1913ea4b2b26d8d00a3936e03f3637ac476cd8d633dc5b5f3e9ebb218","sha256:ba844df294200b73294fe5ae122cc449cf2812b35f15e9c6c58f80f98dabc150"],"state_sha256":"2cf7c675c11f471fa4a1ce388eeb9cae97880483d7c36f385004ba071e355ea4"}