{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:F3O52PITCFDFJF3GGZGC4VCZMC","short_pith_number":"pith:F3O52PIT","canonical_record":{"source":{"id":"1712.05114","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-14T07:34:32Z","cross_cats_sorted":[],"title_canon_sha256":"de0bd3ec0ffd7db40d669e276da0e77c4ed670fd35b88c542d7ed24d10e551b0","abstract_canon_sha256":"2a5e385846a4344af245335f1e029fb6d73ae99350be2f7ae4a7236cca68b208"},"schema_version":"1.0"},"canonical_sha256":"2edddd3d131146549766364c2e545960a4d7a0a894b3dd2fa85ece3ededcc533","source":{"kind":"arxiv","id":"1712.05114","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.05114","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"arxiv_version","alias_value":"1712.05114v1","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.05114","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"pith_short_12","alias_value":"F3O52PITCFDF","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"F3O52PITCFDFJF3G","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"F3O52PIT","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:F3O52PITCFDFJF3GGZGC4VCZMC","target":"record","payload":{"canonical_record":{"source":{"id":"1712.05114","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-14T07:34:32Z","cross_cats_sorted":[],"title_canon_sha256":"de0bd3ec0ffd7db40d669e276da0e77c4ed670fd35b88c542d7ed24d10e551b0","abstract_canon_sha256":"2a5e385846a4344af245335f1e029fb6d73ae99350be2f7ae4a7236cca68b208"},"schema_version":"1.0"},"canonical_sha256":"2edddd3d131146549766364c2e545960a4d7a0a894b3dd2fa85ece3ededcc533","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:28:00.966953Z","signature_b64":"19MATesbjoxWkRja3y+fxtlUFJlnUscvWvKH+tMYwLtztshFBHrFeUSMV4/SH2KQ3XTImHpsWntZpKj5J2wTDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2edddd3d131146549766364c2e545960a4d7a0a894b3dd2fa85ece3ededcc533","last_reissued_at":"2026-05-18T00:28:00.966225Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:28:00.966225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.05114","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":"2026-05-18T00:28:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DHe/iwkuRmsJ4T+h3c8xqX48gcoVfObEO5NF6m/HLU4hobI+donTXBXpQujUU07sMkbZi3Ct2p2bF92EV44/Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T16:51:55.857427Z"},"content_sha256":"dadfc97ddcafd1afea791c4a063575c087b984f95005c56a3e5611b57a27e810","schema_version":"1.0","event_id":"sha256:dadfc97ddcafd1afea791c4a063575c087b984f95005c56a3e5611b57a27e810"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:F3O52PITCFDFJF3GGZGC4VCZMC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by Imitating Physicians","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bin Qiu, Haopeng Liu, Jie He, Kungang Li, Ning Li, Shijun Zhao, Wei Guo","submitted_at":"2017-12-14T07:34:32Z","abstract_excerpt":"This paper proposes a novel and efficient method to build a Computer-Aided Diagnoses (CAD) system for lung nodule detection based on Computed Tomography (CT). This task was treated as an Object Detection on Video (VID) problem by imitating how a radiologist reads CT scans. A lung nodule detector was trained to automatically learn nodule features from still images to detect lung nodule candidates with both high recall and accuracy. Unlike previous work which used 3-dimensional information around the nodule to reduce false positives, we propose two simple but efficient methods, Multi-slice propa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.05114","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":"2026-05-18T00:28:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wL+/2ChZF1jwLwzaebMX2patu9NF/Unk+WekXpRa+UPqeCw5YgdAh8FTo4CPphrppi7/z/pZePyIHis4hNK4Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T16:51:55.858241Z"},"content_sha256":"1c613392764a8ec5d4cb8d1acd22c15f0679f3ad88c656ebb8645307d28fd344","schema_version":"1.0","event_id":"sha256:1c613392764a8ec5d4cb8d1acd22c15f0679f3ad88c656ebb8645307d28fd344"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F3O52PITCFDFJF3GGZGC4VCZMC/bundle.json","state_url":"https://pith.science/pith/F3O52PITCFDFJF3GGZGC4VCZMC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F3O52PITCFDFJF3GGZGC4VCZMC/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":"2026-05-31T16:51:55Z","links":{"resolver":"https://pith.science/pith/F3O52PITCFDFJF3GGZGC4VCZMC","bundle":"https://pith.science/pith/F3O52PITCFDFJF3GGZGC4VCZMC/bundle.json","state":"https://pith.science/pith/F3O52PITCFDFJF3GGZGC4VCZMC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F3O52PITCFDFJF3GGZGC4VCZMC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:F3O52PITCFDFJF3GGZGC4VCZMC","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":"2a5e385846a4344af245335f1e029fb6d73ae99350be2f7ae4a7236cca68b208","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-14T07:34:32Z","title_canon_sha256":"de0bd3ec0ffd7db40d669e276da0e77c4ed670fd35b88c542d7ed24d10e551b0"},"schema_version":"1.0","source":{"id":"1712.05114","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.05114","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"arxiv_version","alias_value":"1712.05114v1","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.05114","created_at":"2026-05-18T00:28:00Z"},{"alias_kind":"pith_short_12","alias_value":"F3O52PITCFDF","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"F3O52PITCFDFJF3G","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"F3O52PIT","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:1c613392764a8ec5d4cb8d1acd22c15f0679f3ad88c656ebb8645307d28fd344","target":"graph","created_at":"2026-05-18T00:28:00Z","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":"This paper proposes a novel and efficient method to build a Computer-Aided Diagnoses (CAD) system for lung nodule detection based on Computed Tomography (CT). This task was treated as an Object Detection on Video (VID) problem by imitating how a radiologist reads CT scans. A lung nodule detector was trained to automatically learn nodule features from still images to detect lung nodule candidates with both high recall and accuracy. Unlike previous work which used 3-dimensional information around the nodule to reduce false positives, we propose two simple but efficient methods, Multi-slice propa","authors_text":"Bin Qiu, Haopeng Liu, Jie He, Kungang Li, Ning Li, Shijun Zhao, Wei Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-14T07:34:32Z","title":"Detection and Attention: Diagnosing Pulmonary Lung Cancer from CT by Imitating Physicians"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.05114","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:dadfc97ddcafd1afea791c4a063575c087b984f95005c56a3e5611b57a27e810","target":"record","created_at":"2026-05-18T00:28:00Z","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":"2a5e385846a4344af245335f1e029fb6d73ae99350be2f7ae4a7236cca68b208","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-14T07:34:32Z","title_canon_sha256":"de0bd3ec0ffd7db40d669e276da0e77c4ed670fd35b88c542d7ed24d10e551b0"},"schema_version":"1.0","source":{"id":"1712.05114","kind":"arxiv","version":1}},"canonical_sha256":"2edddd3d131146549766364c2e545960a4d7a0a894b3dd2fa85ece3ededcc533","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2edddd3d131146549766364c2e545960a4d7a0a894b3dd2fa85ece3ededcc533","first_computed_at":"2026-05-18T00:28:00.966225Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:28:00.966225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"19MATesbjoxWkRja3y+fxtlUFJlnUscvWvKH+tMYwLtztshFBHrFeUSMV4/SH2KQ3XTImHpsWntZpKj5J2wTDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:28:00.966953Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.05114","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dadfc97ddcafd1afea791c4a063575c087b984f95005c56a3e5611b57a27e810","sha256:1c613392764a8ec5d4cb8d1acd22c15f0679f3ad88c656ebb8645307d28fd344"],"state_sha256":"e694ff73501a89810205ffe53e3ea8fcb2d2772bfc5f274f892234b123caa1b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BhN5MKv2y3lz+1LNjoOdT2D/jTFHrkt+HYjoQNwb++ttPyPToupjPZ1SVfVAFTRP4DzNWFNjuyoGyJKr+dcPBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T16:51:55.865964Z","bundle_sha256":"be910110fa5986ba501d6d465c87ad7f09d31b7147565547ef41cfa8a55666b4"}}