{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TTV5NKANMRAWC2Y7HLQ377TDTZ","short_pith_number":"pith:TTV5NKAN","canonical_record":{"source":{"id":"2606.18378","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-16T18:25:59Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"aa2c80b071c6b0760ccfc4c5bc7c2cbac338cc0814d4726dcdd07f40ec8203f3","abstract_canon_sha256":"f6e42d2345543c6661e7aeac973a319698af0fd27b24bc12893102ab8c6d4a0e"},"schema_version":"1.0"},"canonical_sha256":"9cebd6a80d6441616b1f3ae1bffe639e664cd9f1c74bb39a95914b2c34f8be8c","source":{"kind":"arxiv","id":"2606.18378","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.18378","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"arxiv_version","alias_value":"2606.18378v1","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18378","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_12","alias_value":"TTV5NKANMRAW","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_16","alias_value":"TTV5NKANMRAWC2Y7","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_8","alias_value":"TTV5NKAN","created_at":"2026-06-19T16:10:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TTV5NKANMRAWC2Y7HLQ377TDTZ","target":"record","payload":{"canonical_record":{"source":{"id":"2606.18378","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-16T18:25:59Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"aa2c80b071c6b0760ccfc4c5bc7c2cbac338cc0814d4726dcdd07f40ec8203f3","abstract_canon_sha256":"f6e42d2345543c6661e7aeac973a319698af0fd27b24bc12893102ab8c6d4a0e"},"schema_version":"1.0"},"canonical_sha256":"9cebd6a80d6441616b1f3ae1bffe639e664cd9f1c74bb39a95914b2c34f8be8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:10:59.552003Z","signature_b64":"2TwyDVjvl5JyNCgKyx9cUMPaQbo0UsfLsMQqTGpbcmgTtOrb+6dMLltQJk9dZP9pzMDz5dArZzzELiROiVXwCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9cebd6a80d6441616b1f3ae1bffe639e664cd9f1c74bb39a95914b2c34f8be8c","last_reissued_at":"2026-06-19T16:10:59.551609Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:10:59.551609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.18378","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":"2026-06-19T16:10:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mMkB9e5L9KT839ZQrK143QNEtBMfx+WOIjABnkAHYykj867heQrTIUj7yrhO5RlqVCJ0jfOWs7voZs+UetQnCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T10:58:48.485014Z"},"content_sha256":"a98b5cb027ef57bdb8775d55151c0cf424553296693aae923c87a674d6441466","schema_version":"1.0","event_id":"sha256:a98b5cb027ef57bdb8775d55151c0cf424553296693aae923c87a674d6441466"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TTV5NKANMRAWC2Y7HLQ377TDTZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Inferential Models: The Power of Auxiliary Variables for Reasoning with Scientific Uncertainty","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Chuanhai Liu","submitted_at":"2026-06-16T18:25:59Z","abstract_excerpt":"A central challenge in scientific inference is to produce uncertainty assessments that are both situation-specific and frequency-calibrated. This article examines inferential models (IMs) as a framework for prior-free probabilistic reasoning with scientific uncertainty. The central IM idea is to view the auxiliary variables in a sampling model as the source of model-based uncertainty. R. A. Fisher's fiducial inference transfers auxiliary randomness to the parameter space before applying probability calculus; IMs instead predict the unobserved auxiliary value with calibrated predictive random s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18378","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/2606.18378/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":"2026-06-19T16:10:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9zkP+ApI3nKuzXyUTgNI4jr6TFNL8WHhABppLTpLtjsvrwpU/Zi7HVHjN4L3UpxG6zcLoh3dLyNfHOg75KaKAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T10:58:48.485406Z"},"content_sha256":"4acac70208d36ad06ee1b943fc7463ca6fc952eaeb67a6f6c4f36db21454da7b","schema_version":"1.0","event_id":"sha256:4acac70208d36ad06ee1b943fc7463ca6fc952eaeb67a6f6c4f36db21454da7b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/bundle.json","state_url":"https://pith.science/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/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":"2026-06-29T10:58:48Z","links":{"resolver":"https://pith.science/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ","bundle":"https://pith.science/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/bundle.json","state":"https://pith.science/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TTV5NKANMRAWC2Y7HLQ377TDTZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TTV5NKANMRAWC2Y7HLQ377TDTZ","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":"f6e42d2345543c6661e7aeac973a319698af0fd27b24bc12893102ab8c6d4a0e","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-16T18:25:59Z","title_canon_sha256":"aa2c80b071c6b0760ccfc4c5bc7c2cbac338cc0814d4726dcdd07f40ec8203f3"},"schema_version":"1.0","source":{"id":"2606.18378","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.18378","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"arxiv_version","alias_value":"2606.18378v1","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18378","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_12","alias_value":"TTV5NKANMRAW","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_16","alias_value":"TTV5NKANMRAWC2Y7","created_at":"2026-06-19T16:10:59Z"},{"alias_kind":"pith_short_8","alias_value":"TTV5NKAN","created_at":"2026-06-19T16:10:59Z"}],"graph_snapshots":[{"event_id":"sha256:4acac70208d36ad06ee1b943fc7463ca6fc952eaeb67a6f6c4f36db21454da7b","target":"graph","created_at":"2026-06-19T16:10:59Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.18378/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A central challenge in scientific inference is to produce uncertainty assessments that are both situation-specific and frequency-calibrated. This article examines inferential models (IMs) as a framework for prior-free probabilistic reasoning with scientific uncertainty. The central IM idea is to view the auxiliary variables in a sampling model as the source of model-based uncertainty. R. A. Fisher's fiducial inference transfers auxiliary randomness to the parameter space before applying probability calculus; IMs instead predict the unobserved auxiliary value with calibrated predictive random s","authors_text":"Chuanhai Liu","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-16T18:25:59Z","title":"Inferential Models: The Power of Auxiliary Variables for Reasoning with Scientific Uncertainty"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18378","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:a98b5cb027ef57bdb8775d55151c0cf424553296693aae923c87a674d6441466","target":"record","created_at":"2026-06-19T16:10:59Z","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":"f6e42d2345543c6661e7aeac973a319698af0fd27b24bc12893102ab8c6d4a0e","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2026-06-16T18:25:59Z","title_canon_sha256":"aa2c80b071c6b0760ccfc4c5bc7c2cbac338cc0814d4726dcdd07f40ec8203f3"},"schema_version":"1.0","source":{"id":"2606.18378","kind":"arxiv","version":1}},"canonical_sha256":"9cebd6a80d6441616b1f3ae1bffe639e664cd9f1c74bb39a95914b2c34f8be8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9cebd6a80d6441616b1f3ae1bffe639e664cd9f1c74bb39a95914b2c34f8be8c","first_computed_at":"2026-06-19T16:10:59.551609Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:10:59.551609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2TwyDVjvl5JyNCgKyx9cUMPaQbo0UsfLsMQqTGpbcmgTtOrb+6dMLltQJk9dZP9pzMDz5dArZzzELiROiVXwCg==","signature_status":"signed_v1","signed_at":"2026-06-19T16:10:59.552003Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.18378","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a98b5cb027ef57bdb8775d55151c0cf424553296693aae923c87a674d6441466","sha256:4acac70208d36ad06ee1b943fc7463ca6fc952eaeb67a6f6c4f36db21454da7b"],"state_sha256":"65244d758cf7d3f49b920eef8aa3e6c7ca9fc864d9d8ef2bb3c59594ddc9e627"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DaTt3t8d8+4zscZpoJMJbC6nD8TvC+1gCLO9Uai4ZUsO4hOsYHGaoay/gRTgXEi4BEWyQ/pLNx+GuKzznVhQCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T10:58:48.487381Z","bundle_sha256":"8758597d08e59ac07992807ae1efb9d60a39427b9d22748877e2b2310eefaa34"}}