{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:IC3GFTXV23NMOZ7HIE3XNYN3H6","short_pith_number":"pith:IC3GFTXV","canonical_record":{"source":{"id":"2408.12332","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2024-08-22T12:20:17Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"bb13b03a1ae3f0aee140ab3b0af919bd8d622cb017460523b3f92aabeb6356c6","abstract_canon_sha256":"514a10c2d592cd08b3026bc463b930a61d3a06adf4171575af676e23de38c358"},"schema_version":"1.0"},"canonical_sha256":"40b662cef5d6dac767e7413776e1bb3f86e948a4fb6233a61efcabc99c153dc4","source":{"kind":"arxiv","id":"2408.12332","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.12332","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"arxiv_version","alias_value":"2408.12332v4","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.12332","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_12","alias_value":"IC3GFTXV23NM","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_16","alias_value":"IC3GFTXV23NMOZ7H","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_8","alias_value":"IC3GFTXV","created_at":"2026-07-05T11:56:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:IC3GFTXV23NMOZ7HIE3XNYN3H6","target":"record","payload":{"canonical_record":{"source":{"id":"2408.12332","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2024-08-22T12:20:17Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"bb13b03a1ae3f0aee140ab3b0af919bd8d622cb017460523b3f92aabeb6356c6","abstract_canon_sha256":"514a10c2d592cd08b3026bc463b930a61d3a06adf4171575af676e23de38c358"},"schema_version":"1.0"},"canonical_sha256":"40b662cef5d6dac767e7413776e1bb3f86e948a4fb6233a61efcabc99c153dc4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:15.165221Z","signature_b64":"ERwJXPCbEAW4rHz9ScD699ut6n0KgoItwzVpnAbPLW3nu0yvmwU1JvJ2ZcQGvnOLUSjCJZMAwfeHvIdzweK8Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40b662cef5d6dac767e7413776e1bb3f86e948a4fb6233a61efcabc99c153dc4","last_reissued_at":"2026-07-05T11:56:15.164784Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:15.164784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.12332","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:56:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hIDkPAIeArZuPMEP6GpLRu2wnTVCIwQ0rsQl+wAN8jm9FH0aiMRPMNcdTGP8ZAeOAwDW5H/EXWvn0T59prZkCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T11:45:23.808976Z"},"content_sha256":"fcd1d42950f8acf9ddca2592454242098687e29cca6abd177bd82a2f7d92512c","schema_version":"1.0","event_id":"sha256:fcd1d42950f8acf9ddca2592454242098687e29cca6abd177bd82a2f7d92512c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:IC3GFTXV23NMOZ7HIE3XNYN3H6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Simplifying Random Forests' Probabilistic Forecasts","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"stat.AP","authors_text":"Fabian Kr\\\"uger, Nils Koster","submitted_at":"2024-08-22T12:20:17Z","abstract_excerpt":"Since their introduction by Breiman, Random Forests (RFs) have proven to be useful for both classification and regression tasks. The RF prediction of a previously unseen observation can be represented as a weighted sum of all training sample observations. This nearest-neighbor-type representation is useful, among other things, for constructing forecast distributions (Meinshausen, 2006). In this paper, we consider simplifying RF-based forecast distributions by sparsifying them. That is, we focus on a small subset of $k$ nearest neighbors while setting the remaining weights to zero. This simplif"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.12332","kind":"arxiv","version":4},"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/2408.12332/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":"2026-07-05T11:56:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Rd5dr3awLZmjdJfxoniqtj+sOG34fzLqV6d7+2neac4ThHyL5MPKuu1gdlT+EJGm05ZKTQZIVOrDHDPXzgWDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T11:45:23.809381Z"},"content_sha256":"9420777e95795c91de08aa495f22f009825a70b058f9b005851d110f400a8385","schema_version":"1.0","event_id":"sha256:9420777e95795c91de08aa495f22f009825a70b058f9b005851d110f400a8385"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/bundle.json","state_url":"https://pith.science/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/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":"2026-08-22T11:45:23Z","links":{"resolver":"https://pith.science/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6","bundle":"https://pith.science/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/bundle.json","state":"https://pith.science/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IC3GFTXV23NMOZ7HIE3XNYN3H6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IC3GFTXV23NMOZ7HIE3XNYN3H6","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":"514a10c2d592cd08b3026bc463b930a61d3a06adf4171575af676e23de38c358","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2024-08-22T12:20:17Z","title_canon_sha256":"bb13b03a1ae3f0aee140ab3b0af919bd8d622cb017460523b3f92aabeb6356c6"},"schema_version":"1.0","source":{"id":"2408.12332","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.12332","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"arxiv_version","alias_value":"2408.12332v4","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.12332","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_12","alias_value":"IC3GFTXV23NM","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_16","alias_value":"IC3GFTXV23NMOZ7H","created_at":"2026-07-05T11:56:15Z"},{"alias_kind":"pith_short_8","alias_value":"IC3GFTXV","created_at":"2026-07-05T11:56:15Z"}],"graph_snapshots":[{"event_id":"sha256:9420777e95795c91de08aa495f22f009825a70b058f9b005851d110f400a8385","target":"graph","created_at":"2026-07-05T11:56:15Z","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/2408.12332/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Since their introduction by Breiman, Random Forests (RFs) have proven to be useful for both classification and regression tasks. The RF prediction of a previously unseen observation can be represented as a weighted sum of all training sample observations. This nearest-neighbor-type representation is useful, among other things, for constructing forecast distributions (Meinshausen, 2006). In this paper, we consider simplifying RF-based forecast distributions by sparsifying them. That is, we focus on a small subset of $k$ nearest neighbors while setting the remaining weights to zero. This simplif","authors_text":"Fabian Kr\\\"uger, Nils Koster","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2024-08-22T12:20:17Z","title":"Simplifying Random Forests' Probabilistic Forecasts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.12332","kind":"arxiv","version":4},"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:fcd1d42950f8acf9ddca2592454242098687e29cca6abd177bd82a2f7d92512c","target":"record","created_at":"2026-07-05T11:56:15Z","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":"514a10c2d592cd08b3026bc463b930a61d3a06adf4171575af676e23de38c358","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2024-08-22T12:20:17Z","title_canon_sha256":"bb13b03a1ae3f0aee140ab3b0af919bd8d622cb017460523b3f92aabeb6356c6"},"schema_version":"1.0","source":{"id":"2408.12332","kind":"arxiv","version":4}},"canonical_sha256":"40b662cef5d6dac767e7413776e1bb3f86e948a4fb6233a61efcabc99c153dc4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40b662cef5d6dac767e7413776e1bb3f86e948a4fb6233a61efcabc99c153dc4","first_computed_at":"2026-07-05T11:56:15.164784Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:56:15.164784Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ERwJXPCbEAW4rHz9ScD699ut6n0KgoItwzVpnAbPLW3nu0yvmwU1JvJ2ZcQGvnOLUSjCJZMAwfeHvIdzweK8Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:56:15.165221Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.12332","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fcd1d42950f8acf9ddca2592454242098687e29cca6abd177bd82a2f7d92512c","sha256:9420777e95795c91de08aa495f22f009825a70b058f9b005851d110f400a8385"],"state_sha256":"1d3448e56c8cc07b805124b4022c39e68355b8f592da5bf71d8ae9d6a7a1ccd6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mUc8n1Tog6iDdMw9kX1j4xA9J8gDTU2/X64lukKOCU96Xj42hAAZY3PXocJO5gAaXtQJomSMaceHRp7RSPChDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T11:45:23.812671Z","bundle_sha256":"9c9f4d13d16f57ee5fe7fe038a2a294ffb1c97bc9d40cba1ac203980e03c05f2"}}