{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:ZQMSXSAF6FS2DPKZT7ZJXOXZYX","short_pith_number":"pith:ZQMSXSAF","canonical_record":{"source":{"id":"1610.09036","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-27T23:46:19Z","cross_cats_sorted":[],"title_canon_sha256":"6e74c33e54e8c85b7301c3119155cdce8b70240aa4a003fb1a5d0efd09167103","abstract_canon_sha256":"84d7a66c68de9080d10b9803f2a3e7a5a329633d3dca1359d1861393ce3c0c41"},"schema_version":"1.0"},"canonical_sha256":"cc192bc805f165a1bd599ff29bbaf9c5d89b0f7ebeae2b86c501093fd7879432","source":{"kind":"arxiv","id":"1610.09036","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.09036","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"arxiv_version","alias_value":"1610.09036v1","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.09036","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZQMSXSAF6FS2","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"ZQMSXSAF6FS2DPKZ","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"ZQMSXSAF","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:ZQMSXSAF6FS2DPKZT7ZJXOXZYX","target":"record","payload":{"canonical_record":{"source":{"id":"1610.09036","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-27T23:46:19Z","cross_cats_sorted":[],"title_canon_sha256":"6e74c33e54e8c85b7301c3119155cdce8b70240aa4a003fb1a5d0efd09167103","abstract_canon_sha256":"84d7a66c68de9080d10b9803f2a3e7a5a329633d3dca1359d1861393ce3c0c41"},"schema_version":"1.0"},"canonical_sha256":"cc192bc805f165a1bd599ff29bbaf9c5d89b0f7ebeae2b86c501093fd7879432","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:00:59.358178Z","signature_b64":"qVdKA5lzm0B9hWX9Fa6LDwHzsEBJBQeX2dngowUzVu2+W6C6BP5JPbfvnm48BYpf97cSEt0X2ikWNq6Jjm3FAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc192bc805f165a1bd599ff29bbaf9c5d89b0f7ebeae2b86c501093fd7879432","last_reissued_at":"2026-05-18T01:00:59.357272Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:00:59.357272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1610.09036","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:00:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JaED7Kpi/Fj1Q7zuQx+fEKT/0RJaHNhBNQ0/PToy9KQrxDiiXdVURciftVdpNttgHWLIL+j3xatTu89O+Qv5CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:31:32.937730Z"},"content_sha256":"81dd9274d5720ff00e0f1fd8ecc60f9ff9d9bd5bfdba253a28acd02c6fb070d2","schema_version":"1.0","event_id":"sha256:81dd9274d5720ff00e0f1fd8ecc60f9ff9d9bd5bfdba253a28acd02c6fb070d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:ZQMSXSAF6FS2DPKZT7ZJXOXZYX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Interpreting Models via Single Tree Approximation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Giles Hooker, Yichen Zhou","submitted_at":"2016-10-27T23:46:19Z","abstract_excerpt":"We propose a procedure to build a decision tree which approximates the performance of complex machine learning models. This single approximation tree can be used to interpret and simplify the predicting pattern of random forests (RFs) and other models. The use of a tree structure is particularly relevant in medical questionnaires where it enables an adaptive shortening of the questionnaire, reducing response burden. We study the asymptotic behavior of splits and introduce an improved splitting method designed to stabilize tree structure. Empirical studies on both simulation and real data sets "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.09036","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:00:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r1xsmjVCFHyXdKwcyYWk7C4xJyTaANIYhGV30ubObG9NviPLkY5GqbOGCeQaOogeVE+ChU3WOaJ+w30G/bZ+Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:31:32.938232Z"},"content_sha256":"3f46e9575a45965de89269a8019746d2c5e52108702e4ce7c10cd869a888a7b4","schema_version":"1.0","event_id":"sha256:3f46e9575a45965de89269a8019746d2c5e52108702e4ce7c10cd869a888a7b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/bundle.json","state_url":"https://pith.science/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/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":"2026-05-26T11:31:32Z","links":{"resolver":"https://pith.science/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX","bundle":"https://pith.science/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/bundle.json","state":"https://pith.science/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZQMSXSAF6FS2DPKZT7ZJXOXZYX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:ZQMSXSAF6FS2DPKZT7ZJXOXZYX","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":"84d7a66c68de9080d10b9803f2a3e7a5a329633d3dca1359d1861393ce3c0c41","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-27T23:46:19Z","title_canon_sha256":"6e74c33e54e8c85b7301c3119155cdce8b70240aa4a003fb1a5d0efd09167103"},"schema_version":"1.0","source":{"id":"1610.09036","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1610.09036","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"arxiv_version","alias_value":"1610.09036v1","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.09036","created_at":"2026-05-18T01:00:59Z"},{"alias_kind":"pith_short_12","alias_value":"ZQMSXSAF6FS2","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"ZQMSXSAF6FS2DPKZ","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"ZQMSXSAF","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:3f46e9575a45965de89269a8019746d2c5e52108702e4ce7c10cd869a888a7b4","target":"graph","created_at":"2026-05-18T01:00:59Z","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"},"paper":{"abstract_excerpt":"We propose a procedure to build a decision tree which approximates the performance of complex machine learning models. This single approximation tree can be used to interpret and simplify the predicting pattern of random forests (RFs) and other models. The use of a tree structure is particularly relevant in medical questionnaires where it enables an adaptive shortening of the questionnaire, reducing response burden. We study the asymptotic behavior of splits and introduce an improved splitting method designed to stabilize tree structure. Empirical studies on both simulation and real data sets ","authors_text":"Giles Hooker, Yichen Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-27T23:46:19Z","title":"Interpreting Models via Single Tree Approximation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.09036","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":"sha256:81dd9274d5720ff00e0f1fd8ecc60f9ff9d9bd5bfdba253a28acd02c6fb070d2","target":"record","created_at":"2026-05-18T01:00:59Z","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":"84d7a66c68de9080d10b9803f2a3e7a5a329633d3dca1359d1861393ce3c0c41","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-10-27T23:46:19Z","title_canon_sha256":"6e74c33e54e8c85b7301c3119155cdce8b70240aa4a003fb1a5d0efd09167103"},"schema_version":"1.0","source":{"id":"1610.09036","kind":"arxiv","version":1}},"canonical_sha256":"cc192bc805f165a1bd599ff29bbaf9c5d89b0f7ebeae2b86c501093fd7879432","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc192bc805f165a1bd599ff29bbaf9c5d89b0f7ebeae2b86c501093fd7879432","first_computed_at":"2026-05-18T01:00:59.357272Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:00:59.357272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qVdKA5lzm0B9hWX9Fa6LDwHzsEBJBQeX2dngowUzVu2+W6C6BP5JPbfvnm48BYpf97cSEt0X2ikWNq6Jjm3FAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T01:00:59.358178Z","signed_message":"canonical_sha256_bytes"},"source_id":"1610.09036","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:81dd9274d5720ff00e0f1fd8ecc60f9ff9d9bd5bfdba253a28acd02c6fb070d2","sha256:3f46e9575a45965de89269a8019746d2c5e52108702e4ce7c10cd869a888a7b4"],"state_sha256":"9d98e2cb65391df6569b2ac20cb30132c6332e2e10452761c5dcb2563b4a5fda"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jEW2VGlxIQrbH431hVpbqNDr5tigJBHxYD9l33/EMz423+sgtt3W9qqDaw5DRzrtJwjBmMIR/fxT8cHRGptTBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T11:31:32.941158Z","bundle_sha256":"ea7c0f7053d07869a2fdd8f61bad95383e96a16b020fb65555be16ad848db31c"}}