{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:XRDCS6ABVOQBELYFGAZZKX2WIZ","short_pith_number":"pith:XRDCS6AB","canonical_record":{"source":{"id":"2402.00015","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-28T14:14:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ffa6410535abff8b39c7a0ee722b850dd7bb6b59998c1e13e1d2c31471910dfe","abstract_canon_sha256":"7dc53c70abc594007480beb1d4b4b6619b44d8cc7a7c05074d0a338a9f97ce53"},"schema_version":"1.0"},"canonical_sha256":"bc46297801aba0122f053033955f56466ad8d62967663ba809a9257dfe0f97ce","source":{"kind":"arxiv","id":"2402.00015","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00015","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00015v2","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00015","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_12","alias_value":"XRDCS6ABVOQB","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_16","alias_value":"XRDCS6ABVOQBELYF","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_8","alias_value":"XRDCS6AB","created_at":"2026-07-05T08:08:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:XRDCS6ABVOQBELYFGAZZKX2WIZ","target":"record","payload":{"canonical_record":{"source":{"id":"2402.00015","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-28T14:14:31Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"ffa6410535abff8b39c7a0ee722b850dd7bb6b59998c1e13e1d2c31471910dfe","abstract_canon_sha256":"7dc53c70abc594007480beb1d4b4b6619b44d8cc7a7c05074d0a338a9f97ce53"},"schema_version":"1.0"},"canonical_sha256":"bc46297801aba0122f053033955f56466ad8d62967663ba809a9257dfe0f97ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:01.574151Z","signature_b64":"7L1Ulz2XYFNsX9/3thGPwiy5h7yqBKRfjS7nycwUHEw1Ifa6f2x14Y0vvndDdvIkyqDazvTlrqZyeGU3ZGtbBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc46297801aba0122f053033955f56466ad8d62967663ba809a9257dfe0f97ce","last_reissued_at":"2026-07-05T08:08:01.573607Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:01.573607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.00015","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:08:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZPito2ELU1+sZ3C/42J/k4nw6E9qX4xLOI5JZnWRmIe98IOzpvok0+5Yq/z/uKBCjmzeNH1aeNQRCPeoE0TOCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T20:51:16.657858Z"},"content_sha256":"147692c4b891e376c31b4212439ed90a9703b28cb6a84c86b092a7277e35a36b","schema_version":"1.0","event_id":"sha256:147692c4b891e376c31b4212439ed90a9703b28cb6a84c86b092a7277e35a36b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:XRDCS6ABVOQBELYFGAZZKX2WIZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Maintaining User Trust Through Multistage Uncertainty Aware Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.AI","authors_text":"Ashish Papanai, Chandan Agrawal, Jerome White","submitted_at":"2023-12-28T14:14:31Z","abstract_excerpt":"This paper describes and evaluates a multistage approach to AI deployment. Each stage involves a more accurate method of inference, yet engaging each comes with an increasing cost. In outlining the architecture, we present a method for quantifying model uncertainty that facilitates confident deferral decisions. The architecture is currently under active deployment to thousands of cotton farmers across India. The broader idea however is applicable to a growing sector of AI deployments in challenging low resources settings."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00015","kind":"arxiv","version":2},"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/2402.00015/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":"2026-07-05T08:08:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZmaB7vfiqUhmpaOBGH90m9IhmsJ9Djo5nv0x5Xy2DnqLO+pdaYtNJ5Qx5ni6V/JOwvos/EhwXJvDbPI1BFdNCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T20:51:16.658228Z"},"content_sha256":"832e151b0ae420d8d4e5018551b21802e2e5191facf0511905d6da2c9c4f41d5","schema_version":"1.0","event_id":"sha256:832e151b0ae420d8d4e5018551b21802e2e5191facf0511905d6da2c9c4f41d5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/bundle.json","state_url":"https://pith.science/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/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":"2026-07-08T20:51:16Z","links":{"resolver":"https://pith.science/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ","bundle":"https://pith.science/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/bundle.json","state":"https://pith.science/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XRDCS6ABVOQBELYFGAZZKX2WIZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XRDCS6ABVOQBELYFGAZZKX2WIZ","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":"7dc53c70abc594007480beb1d4b4b6619b44d8cc7a7c05074d0a338a9f97ce53","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-28T14:14:31Z","title_canon_sha256":"ffa6410535abff8b39c7a0ee722b850dd7bb6b59998c1e13e1d2c31471910dfe"},"schema_version":"1.0","source":{"id":"2402.00015","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00015","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00015v2","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00015","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_12","alias_value":"XRDCS6ABVOQB","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_16","alias_value":"XRDCS6ABVOQBELYF","created_at":"2026-07-05T08:08:01Z"},{"alias_kind":"pith_short_8","alias_value":"XRDCS6AB","created_at":"2026-07-05T08:08:01Z"}],"graph_snapshots":[{"event_id":"sha256:832e151b0ae420d8d4e5018551b21802e2e5191facf0511905d6da2c9c4f41d5","target":"graph","created_at":"2026-07-05T08:08:01Z","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/2402.00015/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper describes and evaluates a multistage approach to AI deployment. Each stage involves a more accurate method of inference, yet engaging each comes with an increasing cost. In outlining the architecture, we present a method for quantifying model uncertainty that facilitates confident deferral decisions. The architecture is currently under active deployment to thousands of cotton farmers across India. The broader idea however is applicable to a growing sector of AI deployments in challenging low resources settings.","authors_text":"Ashish Papanai, Chandan Agrawal, Jerome White","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-28T14:14:31Z","title":"Maintaining User Trust Through Multistage Uncertainty Aware Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00015","kind":"arxiv","version":2},"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":"sha256:147692c4b891e376c31b4212439ed90a9703b28cb6a84c86b092a7277e35a36b","target":"record","created_at":"2026-07-05T08:08:01Z","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":"7dc53c70abc594007480beb1d4b4b6619b44d8cc7a7c05074d0a338a9f97ce53","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-28T14:14:31Z","title_canon_sha256":"ffa6410535abff8b39c7a0ee722b850dd7bb6b59998c1e13e1d2c31471910dfe"},"schema_version":"1.0","source":{"id":"2402.00015","kind":"arxiv","version":2}},"canonical_sha256":"bc46297801aba0122f053033955f56466ad8d62967663ba809a9257dfe0f97ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc46297801aba0122f053033955f56466ad8d62967663ba809a9257dfe0f97ce","first_computed_at":"2026-07-05T08:08:01.573607Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:01.573607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7L1Ulz2XYFNsX9/3thGPwiy5h7yqBKRfjS7nycwUHEw1Ifa6f2x14Y0vvndDdvIkyqDazvTlrqZyeGU3ZGtbBw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:01.574151Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00015","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:147692c4b891e376c31b4212439ed90a9703b28cb6a84c86b092a7277e35a36b","sha256:832e151b0ae420d8d4e5018551b21802e2e5191facf0511905d6da2c9c4f41d5"],"state_sha256":"5552aa2d2bf38891388f25aff3535f7dc3bf2dc41ae577696ac1fe0f10401a46"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WcW2jcJ6E+QbwYSTS5Wn6d7DPBXatl5Bfbfv6k2HHlx8gPVM9gf6KIM0nnNmber/dEZU5lN1r3+ubGUv9PgTCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T20:51:16.660152Z","bundle_sha256":"65a0ee326a88db1dcdeccc5ba95c0040e80e8324d844933d5d789efdceadbe62"}}