{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:MLA7WMM5TE543VNAAWM57IX25C","short_pith_number":"pith:MLA7WMM5","canonical_record":{"source":{"id":"1911.03740","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-09T17:08:34Z","cross_cats_sorted":["cs.CV","cs.LG","eess.SP","stat.ML"],"title_canon_sha256":"d89ec3d28aee60d04fd792044a18f63d60c164261e12b9c70a7671f476dcc9b6","abstract_canon_sha256":"f284919cd861097688bd4bef352d0fe01856d58d1d9373a965134dfdce6d07ad"},"schema_version":"1.0"},"canonical_sha256":"62c1fb319d993bcdd5a00599dfa2fae8b4a94cc59444c6b3ef58235b4b3bc36a","source":{"kind":"arxiv","id":"1911.03740","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.03740","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"arxiv_version","alias_value":"1911.03740v3","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.03740","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_12","alias_value":"MLA7WMM5TE54","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_16","alias_value":"MLA7WMM5TE543VNA","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_8","alias_value":"MLA7WMM5","created_at":"2026-07-05T00:52:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:MLA7WMM5TE543VNAAWM57IX25C","target":"record","payload":{"canonical_record":{"source":{"id":"1911.03740","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-09T17:08:34Z","cross_cats_sorted":["cs.CV","cs.LG","eess.SP","stat.ML"],"title_canon_sha256":"d89ec3d28aee60d04fd792044a18f63d60c164261e12b9c70a7671f476dcc9b6","abstract_canon_sha256":"f284919cd861097688bd4bef352d0fe01856d58d1d9373a965134dfdce6d07ad"},"schema_version":"1.0"},"canonical_sha256":"62c1fb319d993bcdd5a00599dfa2fae8b4a94cc59444c6b3ef58235b4b3bc36a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:52:48.832030Z","signature_b64":"MtrUk/Lxgi3xO9UzWxYSM3ZOXkIJOoc5J2q1PD4zlDkRR6CraRuJC0Uzikx9m1/sObUqg3jmdbUlVpisWrmBDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62c1fb319d993bcdd5a00599dfa2fae8b4a94cc59444c6b3ef58235b4b3bc36a","last_reissued_at":"2026-07-05T00:52:48.831486Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:52:48.831486Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.03740","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:52:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B5fL9wzmnH29jqiQCaza7iX+Xw8IV7LfrE1B2Pm5s4XbnOnQ1aBChn+/VnwVKcU9xiuwMuJAZfRLOwOtQMkfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:57:51.529419Z"},"content_sha256":"c504f1f5d0c183b999be5e03bc32261f712c8e5751a6fe656028670029051bb1","schema_version":"1.0","event_id":"sha256:c504f1f5d0c183b999be5e03bc32261f712c8e5751a6fe656028670029051bb1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:MLA7WMM5TE543VNAAWM57IX25C","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the design of convolutional neural networks for automatic detection of Alzheimer's disease","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG","eess.SP","stat.ML"],"primary_cat":"eess.IV","authors_text":"Carlos Fernandez-Granda, Chhavi Yadav, Narges Razavian, Sheng Liu","submitted_at":"2019-11-09T17:08:34Z","abstract_excerpt":"Early detection is a crucial goal in the study of Alzheimer's Disease (AD). In this work, we describe several techniques to boost the performance of 3D deep convolutional neural networks (CNNs) trained to detect AD using structural brain MRI scans. Specifically, we provide evidence that (1) instance normalization outperforms batch normalization, (2) early spatial downsampling negatively affects performance, (3) widening the model brings consistent gains while increasing the depth does not, and (4) incorporating age information yields moderate improvement. Together, these insights yield an incr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.03740","kind":"arxiv","version":3},"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/1911.03740/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":"2026-07-05T00:52:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2EtsGzmsMdVIXJWwluQ1cw679iVPFDn7LeNN7QRJRWTUqW437+JhLp64oe9zkxwjH/ycHQcWLnvTSXkuRyN5BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:57:51.529926Z"},"content_sha256":"bf9d28c28e7bf54dd22b3156b82fe4386a92be1f5d08f7f50872869fb023fc64","schema_version":"1.0","event_id":"sha256:bf9d28c28e7bf54dd22b3156b82fe4386a92be1f5d08f7f50872869fb023fc64"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MLA7WMM5TE543VNAAWM57IX25C/bundle.json","state_url":"https://pith.science/pith/MLA7WMM5TE543VNAAWM57IX25C/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MLA7WMM5TE543VNAAWM57IX25C/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":"2026-08-05T02:57:51Z","links":{"resolver":"https://pith.science/pith/MLA7WMM5TE543VNAAWM57IX25C","bundle":"https://pith.science/pith/MLA7WMM5TE543VNAAWM57IX25C/bundle.json","state":"https://pith.science/pith/MLA7WMM5TE543VNAAWM57IX25C/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MLA7WMM5TE543VNAAWM57IX25C/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MLA7WMM5TE543VNAAWM57IX25C","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":"f284919cd861097688bd4bef352d0fe01856d58d1d9373a965134dfdce6d07ad","cross_cats_sorted":["cs.CV","cs.LG","eess.SP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-09T17:08:34Z","title_canon_sha256":"d89ec3d28aee60d04fd792044a18f63d60c164261e12b9c70a7671f476dcc9b6"},"schema_version":"1.0","source":{"id":"1911.03740","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.03740","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"arxiv_version","alias_value":"1911.03740v3","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.03740","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_12","alias_value":"MLA7WMM5TE54","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_16","alias_value":"MLA7WMM5TE543VNA","created_at":"2026-07-05T00:52:48Z"},{"alias_kind":"pith_short_8","alias_value":"MLA7WMM5","created_at":"2026-07-05T00:52:48Z"}],"graph_snapshots":[{"event_id":"sha256:bf9d28c28e7bf54dd22b3156b82fe4386a92be1f5d08f7f50872869fb023fc64","target":"graph","created_at":"2026-07-05T00:52:48Z","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/1911.03740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Early detection is a crucial goal in the study of Alzheimer's Disease (AD). In this work, we describe several techniques to boost the performance of 3D deep convolutional neural networks (CNNs) trained to detect AD using structural brain MRI scans. Specifically, we provide evidence that (1) instance normalization outperforms batch normalization, (2) early spatial downsampling negatively affects performance, (3) widening the model brings consistent gains while increasing the depth does not, and (4) incorporating age information yields moderate improvement. Together, these insights yield an incr","authors_text":"Carlos Fernandez-Granda, Chhavi Yadav, Narges Razavian, Sheng Liu","cross_cats":["cs.CV","cs.LG","eess.SP","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-09T17:08:34Z","title":"On the design of convolutional neural networks for automatic detection of Alzheimer's disease"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.03740","kind":"arxiv","version":3},"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:c504f1f5d0c183b999be5e03bc32261f712c8e5751a6fe656028670029051bb1","target":"record","created_at":"2026-07-05T00:52:48Z","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":"f284919cd861097688bd4bef352d0fe01856d58d1d9373a965134dfdce6d07ad","cross_cats_sorted":["cs.CV","cs.LG","eess.SP","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-11-09T17:08:34Z","title_canon_sha256":"d89ec3d28aee60d04fd792044a18f63d60c164261e12b9c70a7671f476dcc9b6"},"schema_version":"1.0","source":{"id":"1911.03740","kind":"arxiv","version":3}},"canonical_sha256":"62c1fb319d993bcdd5a00599dfa2fae8b4a94cc59444c6b3ef58235b4b3bc36a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"62c1fb319d993bcdd5a00599dfa2fae8b4a94cc59444c6b3ef58235b4b3bc36a","first_computed_at":"2026-07-05T00:52:48.831486Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:52:48.831486Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MtrUk/Lxgi3xO9UzWxYSM3ZOXkIJOoc5J2q1PD4zlDkRR6CraRuJC0Uzikx9m1/sObUqg3jmdbUlVpisWrmBDA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:52:48.832030Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.03740","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c504f1f5d0c183b999be5e03bc32261f712c8e5751a6fe656028670029051bb1","sha256:bf9d28c28e7bf54dd22b3156b82fe4386a92be1f5d08f7f50872869fb023fc64"],"state_sha256":"a687cdf11663814ba027388fc8ded8a4a8afff8130a40b2067035692bcafc0fa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"559XNnz5LmQSfV+j1kv61KkEWkyqCvEEtRe3vpI7SGea8f01XIlNecZuLm3fVwrk1XKzAjs82cWNH/NSZ3w6Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:57:51.535476Z","bundle_sha256":"001a7a7a25284cef96d1f2ae84bb13162e7c7acdea607a452099bf895ace08f7"}}