{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QY6YYVCH3DGMSN4ZG5V56G3PXW","short_pith_number":"pith:QY6YYVCH","canonical_record":{"source":{"id":"2507.01279","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-02T01:36:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bfe9323979db7f42a9a4344c9cc3507797ca7ac120e9792199f7774a9565bdeb","abstract_canon_sha256":"a001a208ca0b167fd97320e8d63ccfc88aaf56e00d9b34694484c8187b8435a1"},"schema_version":"1.0"},"canonical_sha256":"863d8c5447d8ccc93799376bdf1b6fbda42f2248b0288039ab323f2a677526d2","source":{"kind":"arxiv","id":"2507.01279","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.01279","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"arxiv_version","alias_value":"2507.01279v1","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01279","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_12","alias_value":"QY6YYVCH3DGM","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_16","alias_value":"QY6YYVCH3DGMSN4Z","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_8","alias_value":"QY6YYVCH","created_at":"2026-07-05T11:30:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QY6YYVCH3DGMSN4ZG5V56G3PXW","target":"record","payload":{"canonical_record":{"source":{"id":"2507.01279","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-02T01:36:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bfe9323979db7f42a9a4344c9cc3507797ca7ac120e9792199f7774a9565bdeb","abstract_canon_sha256":"a001a208ca0b167fd97320e8d63ccfc88aaf56e00d9b34694484c8187b8435a1"},"schema_version":"1.0"},"canonical_sha256":"863d8c5447d8ccc93799376bdf1b6fbda42f2248b0288039ab323f2a677526d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:30:28.014432Z","signature_b64":"FpzUgrXeZqwS2pvHchsuLCv8QbetDOwGktjDJSaFOPCGneeFZsIH5j75928GoiWcHaj3sgQoiGPZjU/deoMMBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"863d8c5447d8ccc93799376bdf1b6fbda42f2248b0288039ab323f2a677526d2","last_reissued_at":"2026-07-05T11:30:28.013891Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:30:28.013891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.01279","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":"2026-07-05T11:30:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XsEVBJRRxBttvE3xHaStVgfJLrj/rBJeCpRiPQ9z1BjfKfpcsieXXS9jY+M05wXuRi6OdTNmo4JmoqL/HJHyBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:56:13.408542Z"},"content_sha256":"93edcfa94d3b747934ae2dd2f6999cc674d2dac030e403c14e5d79a55e82cc41","schema_version":"1.0","event_id":"sha256:93edcfa94d3b747934ae2dd2f6999cc674d2dac030e403c14e5d79a55e82cc41"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QY6YYVCH3DGMSN4ZG5V56G3PXW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Classification based deep learning models for lung cancer and disease using medical images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Ahmad Chaddad, Jihao Peng, Yihang Wu","submitted_at":"2025-07-02T01:36:29Z","abstract_excerpt":"The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural network (CNN) model, named ResNet+, which is based on the established ResNet framework. This model is specifically designed to improve the prediction of lung cancer and diseases using the images. To address the challenge of missing feature information that occurs during the downsampling process in CNNs, we integrate the ResNet-D module, a variant designed to enhance feature extraction capabilities by modifying the d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01279","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/2507.01279/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":"2026-07-05T11:30:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rM3zJny/0KpVXKJVOPBBSzQjjaZiZDVdGPDXXKiONKEDmwiNjbPxwBEEk7ISJE5/Wx8caxDc498ojV7VRLMNCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:56:13.409099Z"},"content_sha256":"b7aa15d6df0496c9a26eab07d4541307254be041eb4b784090f3c1885142820a","schema_version":"1.0","event_id":"sha256:b7aa15d6df0496c9a26eab07d4541307254be041eb4b784090f3c1885142820a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/bundle.json","state_url":"https://pith.science/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/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":"2026-08-09T05:56:13Z","links":{"resolver":"https://pith.science/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW","bundle":"https://pith.science/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/bundle.json","state":"https://pith.science/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QY6YYVCH3DGMSN4ZG5V56G3PXW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QY6YYVCH3DGMSN4ZG5V56G3PXW","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":"a001a208ca0b167fd97320e8d63ccfc88aaf56e00d9b34694484c8187b8435a1","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-02T01:36:29Z","title_canon_sha256":"bfe9323979db7f42a9a4344c9cc3507797ca7ac120e9792199f7774a9565bdeb"},"schema_version":"1.0","source":{"id":"2507.01279","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.01279","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"arxiv_version","alias_value":"2507.01279v1","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.01279","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_12","alias_value":"QY6YYVCH3DGM","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_16","alias_value":"QY6YYVCH3DGMSN4Z","created_at":"2026-07-05T11:30:28Z"},{"alias_kind":"pith_short_8","alias_value":"QY6YYVCH","created_at":"2026-07-05T11:30:28Z"}],"graph_snapshots":[{"event_id":"sha256:b7aa15d6df0496c9a26eab07d4541307254be041eb4b784090f3c1885142820a","target":"graph","created_at":"2026-07-05T11:30:28Z","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/2507.01279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural network (CNN) model, named ResNet+, which is based on the established ResNet framework. This model is specifically designed to improve the prediction of lung cancer and diseases using the images. To address the challenge of missing feature information that occurs during the downsampling process in CNNs, we integrate the ResNet-D module, a variant designed to enhance feature extraction capabilities by modifying the d","authors_text":"Ahmad Chaddad, Jihao Peng, Yihang Wu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-02T01:36:29Z","title":"Classification based deep learning models for lung cancer and disease using medical images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.01279","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":"sha256:93edcfa94d3b747934ae2dd2f6999cc674d2dac030e403c14e5d79a55e82cc41","target":"record","created_at":"2026-07-05T11:30:28Z","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":"a001a208ca0b167fd97320e8d63ccfc88aaf56e00d9b34694484c8187b8435a1","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-07-02T01:36:29Z","title_canon_sha256":"bfe9323979db7f42a9a4344c9cc3507797ca7ac120e9792199f7774a9565bdeb"},"schema_version":"1.0","source":{"id":"2507.01279","kind":"arxiv","version":1}},"canonical_sha256":"863d8c5447d8ccc93799376bdf1b6fbda42f2248b0288039ab323f2a677526d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"863d8c5447d8ccc93799376bdf1b6fbda42f2248b0288039ab323f2a677526d2","first_computed_at":"2026-07-05T11:30:28.013891Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:30:28.013891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FpzUgrXeZqwS2pvHchsuLCv8QbetDOwGktjDJSaFOPCGneeFZsIH5j75928GoiWcHaj3sgQoiGPZjU/deoMMBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:30:28.014432Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.01279","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:93edcfa94d3b747934ae2dd2f6999cc674d2dac030e403c14e5d79a55e82cc41","sha256:b7aa15d6df0496c9a26eab07d4541307254be041eb4b784090f3c1885142820a"],"state_sha256":"82e7a712a4a258f8786155959b53f69351fd7ae94edceac77644d09fab683f6d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yhL+Xvm0/joHSDNJdwIcn+F56Z7a3DKr05vTStsdZSjBQjQ+jk9zkvkBr++CjJRQ2Te9rcK3WFgNQQmfXZwcBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:56:13.413491Z","bundle_sha256":"6ab7133caf6222d122abdd8b23ab726cc2661efada14efaaea9a838693211750"}}