{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:HBE7HGRALFLRFNRBTG2AMSWPRF","short_pith_number":"pith:HBE7HGRA","canonical_record":{"source":{"id":"2607.26580","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T08:00:11Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3bc2e4d766d2bf27cfbd4b241c40d02e05fe2d9d6643ea3a9317928459bf95a0","abstract_canon_sha256":"5034f8395747d572b64c7fc12edd3a7bcd8523e323ce43c0018216b39a34d6d8"},"schema_version":"1.0"},"canonical_sha256":"3849f39a20595712b62199b4064acf897f3a2842bc5177859f48aa801f239836","source":{"kind":"arxiv","id":"2607.26580","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.26580","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"2607.26580v1","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.26580","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"HBE7HGRALFLR","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_16","alias_value":"HBE7HGRALFLRFNRB","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_8","alias_value":"HBE7HGRA","created_at":"2026-07-30T01:21:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:HBE7HGRALFLRFNRBTG2AMSWPRF","target":"record","payload":{"canonical_record":{"source":{"id":"2607.26580","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T08:00:11Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3bc2e4d766d2bf27cfbd4b241c40d02e05fe2d9d6643ea3a9317928459bf95a0","abstract_canon_sha256":"5034f8395747d572b64c7fc12edd3a7bcd8523e323ce43c0018216b39a34d6d8"},"schema_version":"1.0"},"canonical_sha256":"3849f39a20595712b62199b4064acf897f3a2842bc5177859f48aa801f239836","receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3849f39a20595712b62199b4064acf897f3a2842bc5177859f48aa801f239836","last_reissued_at":"2026-07-30T01:21:04.456159Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-30T01:21:04.456159Z"},"source_kind":"arxiv","source_id":"2607.26580","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":"2026-07-30T01:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oI7TRijddYosNTuoZyiZ/W5lG7zhmxt6euJ4CTCZHYRnkksvg4S1bFm/KTxmWA7iguC4AcfkYTVytmAXqOQeAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:21:00.425037Z"},"content_sha256":"26754a14ee303a4eef74db6c534dc00e7724ae0ffb3f1395850b57f6465e2727","schema_version":"1.0","event_id":"sha256:26754a14ee303a4eef74db6c534dc00e7724ae0ffb3f1395850b57f6465e2727"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:HBE7HGRALFLRFNRBTG2AMSWPRF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Classification of Disease from Lungs X-ray Images using VGG16, VGG19 and ResNet50 Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Nand Lal Yadav, Rajesh Kumar, Satyendra Singh, Sudhakar Singh","submitted_at":"2026-07-29T08:00:11Z","abstract_excerpt":"With the increase in the number of cases related to respiratory diseases, there is an urgent need to detect them early and diagnose them accurately. Convolutional neural networks have given promising results when used for diagnosing diseases using imaging tests. In this study, we investigate the potential of applying deep learning algorithms such as VGG16, VGG19, and ResNet50 for classification of lung ailments based on X-ray images. A detailed analysis of the aforementioned models' performances was conducted to assess how well they can classify various types of lung ailments, including pneumo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.26580","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/2607.26580/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":"2026-07-30T01:21:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f+jFOUGuDyKvFGwKnxSpyzfo9+TKGbN49+1Ejml6TKgOdoS/1dQ08bZz7oIjCpjYSgevczUY/0fyAC0H5FUDCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:21:00.425535Z"},"content_sha256":"c7696eb85f33fe297b49455f1868ec5debbcc219761cc1c230497ca253332491","schema_version":"1.0","event_id":"sha256:c7696eb85f33fe297b49455f1868ec5debbcc219761cc1c230497ca253332491"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/bundle.json","state_url":"https://pith.science/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/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":"2026-08-04T22:21:00Z","links":{"resolver":"https://pith.science/pith/HBE7HGRALFLRFNRBTG2AMSWPRF","bundle":"https://pith.science/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/bundle.json","state":"https://pith.science/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HBE7HGRALFLRFNRBTG2AMSWPRF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HBE7HGRALFLRFNRBTG2AMSWPRF","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":"5034f8395747d572b64c7fc12edd3a7bcd8523e323ce43c0018216b39a34d6d8","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T08:00:11Z","title_canon_sha256":"3bc2e4d766d2bf27cfbd4b241c40d02e05fe2d9d6643ea3a9317928459bf95a0"},"schema_version":"1.0","source":{"id":"2607.26580","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.26580","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"arxiv_version","alias_value":"2607.26580v1","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.26580","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_12","alias_value":"HBE7HGRALFLR","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_16","alias_value":"HBE7HGRALFLRFNRB","created_at":"2026-07-30T01:21:04Z"},{"alias_kind":"pith_short_8","alias_value":"HBE7HGRA","created_at":"2026-07-30T01:21:04Z"}],"graph_snapshots":[{"event_id":"sha256:c7696eb85f33fe297b49455f1868ec5debbcc219761cc1c230497ca253332491","target":"graph","created_at":"2026-07-30T01:21:04Z","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/2607.26580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the increase in the number of cases related to respiratory diseases, there is an urgent need to detect them early and diagnose them accurately. Convolutional neural networks have given promising results when used for diagnosing diseases using imaging tests. In this study, we investigate the potential of applying deep learning algorithms such as VGG16, VGG19, and ResNet50 for classification of lung ailments based on X-ray images. A detailed analysis of the aforementioned models' performances was conducted to assess how well they can classify various types of lung ailments, including pneumo","authors_text":"Nand Lal Yadav, Rajesh Kumar, Satyendra Singh, Sudhakar Singh","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T08:00:11Z","title":"Classification of Disease from Lungs X-ray Images using VGG16, VGG19 and ResNet50 Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.26580","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":"sha256:26754a14ee303a4eef74db6c534dc00e7724ae0ffb3f1395850b57f6465e2727","target":"record","created_at":"2026-07-30T01:21:04Z","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":"5034f8395747d572b64c7fc12edd3a7bcd8523e323ce43c0018216b39a34d6d8","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-29T08:00:11Z","title_canon_sha256":"3bc2e4d766d2bf27cfbd4b241c40d02e05fe2d9d6643ea3a9317928459bf95a0"},"schema_version":"1.0","source":{"id":"2607.26580","kind":"arxiv","version":1}},"canonical_sha256":"3849f39a20595712b62199b4064acf897f3a2842bc5177859f48aa801f239836","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3849f39a20595712b62199b4064acf897f3a2842bc5177859f48aa801f239836","first_computed_at":"2026-07-30T01:21:04.456159Z","kind":"pith_receipt","last_reissued_at":"2026-07-30T01:21:04.456159Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2607.26580","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:26754a14ee303a4eef74db6c534dc00e7724ae0ffb3f1395850b57f6465e2727","sha256:c7696eb85f33fe297b49455f1868ec5debbcc219761cc1c230497ca253332491"],"state_sha256":"7c82531c779371d6031647f97fe0d881d0b95eef91cc3f518c0e7bad46010e43"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pc2UHrzxoNNlHjhrA4QB1cWCEUrGpj9VlT1l/Iu0OegIjgSKpS9v8S0vZ8ZcmHzOGZhNPrEo7ZB3b4bzfwyvAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T22:21:00.431148Z","bundle_sha256":"2661f7f5e6423e2563b9feb0bffe0e7c90bf984fe51a448daf0083457eac33a0"}}