{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:HATZ44FDX2TSQY6B6ZAXBQ4MMO","short_pith_number":"pith:HATZ44FD","canonical_record":{"source":{"id":"2105.05482","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-05-12T07:39:30Z","cross_cats_sorted":["physics.flu-dyn"],"title_canon_sha256":"333b23f3471b50665e36830c5c4090005df9a83fefe51291f36a0972888aed6d","abstract_canon_sha256":"fe4499900bf43ba86ddb40ab1747e3d9678f85ccbb0946aeffd8e29cd6a76134"},"schema_version":"1.0"},"canonical_sha256":"38279e70a3bea72863c1f64170c38c63ba3a96b2bcc345fc1e04d4e221c54a34","source":{"kind":"arxiv","id":"2105.05482","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.05482","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"arxiv_version","alias_value":"2105.05482v1","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.05482","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_12","alias_value":"HATZ44FDX2TS","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_16","alias_value":"HATZ44FDX2TSQY6B","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_8","alias_value":"HATZ44FD","created_at":"2026-07-05T02:44:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:HATZ44FDX2TSQY6B6ZAXBQ4MMO","target":"record","payload":{"canonical_record":{"source":{"id":"2105.05482","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-05-12T07:39:30Z","cross_cats_sorted":["physics.flu-dyn"],"title_canon_sha256":"333b23f3471b50665e36830c5c4090005df9a83fefe51291f36a0972888aed6d","abstract_canon_sha256":"fe4499900bf43ba86ddb40ab1747e3d9678f85ccbb0946aeffd8e29cd6a76134"},"schema_version":"1.0"},"canonical_sha256":"38279e70a3bea72863c1f64170c38c63ba3a96b2bcc345fc1e04d4e221c54a34","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:44:37.481311Z","signature_b64":"LnNj/rp7tE5J53GBalDXLmVH3FFGKte95LCoTzXcW9X+hhVYGSYbDfGdfW29Y2QYT62qwzNMP6I9FMR1oriUDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38279e70a3bea72863c1f64170c38c63ba3a96b2bcc345fc1e04d4e221c54a34","last_reissued_at":"2026-07-05T02:44:37.480864Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:44:37.480864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.05482","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":"2026-07-05T02:44:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/xdQOFX9l7bNdBFdLrSbzIhm1QNvTuES+G45txUYuh5Oy4n+vrgXn1W06NlfHWKHwDe2EeuP1OTLWU9HakgdDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:37:00.927663Z"},"content_sha256":"0034c1b5ae7bd1520f078c94151bc1dc461e42d931efc41c0904e2045dcf8842","schema_version":"1.0","event_id":"sha256:0034c1b5ae7bd1520f078c94151bc1dc461e42d931efc41c0904e2045dcf8842"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:HATZ44FDX2TSQY6B6ZAXBQ4MMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["physics.flu-dyn"],"primary_cat":"cs.LG","authors_text":"Antonio Alguacil, Micha\\\"el Bauerheim, Wagner Gon\\c{c}alves Pinto","submitted_at":"2021-05-12T07:39:30Z","abstract_excerpt":"Reproducibility of a deep-learning fully convolutional neural network is evaluated by training several times the same network on identical conditions (database, hyperparameters, hardware) with non-deterministic Graphics Processings Unit (GPU) operations. The propagation of two-dimensional acoustic waves, typical of time-space evolving physical systems, is studied on both recursive and non-recursive tasks. Significant changes in models properties (weights, featured fields) are observed. When tested on various propagation benchmarks, these models systematically returned estimations with a high l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.05482","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/2105.05482/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":"2026-07-05T02:44:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lv8fePM45wH3P5zwreC+r1wwbpzrOCm3kBp4G4cl9ImypEQxk5jGzG5sEa2OTugBSWsq0f6fxFv2eg47NAisAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:37:00.928163Z"},"content_sha256":"9b48e3c8ace78e654188e01f04be18fcaaac8825f625946f53d0f82a15231f72","schema_version":"1.0","event_id":"sha256:9b48e3c8ace78e654188e01f04be18fcaaac8825f625946f53d0f82a15231f72"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/bundle.json","state_url":"https://pith.science/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/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":"2026-08-08T18:37:00Z","links":{"resolver":"https://pith.science/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO","bundle":"https://pith.science/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/bundle.json","state":"https://pith.science/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HATZ44FDX2TSQY6B6ZAXBQ4MMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:HATZ44FDX2TSQY6B6ZAXBQ4MMO","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":"fe4499900bf43ba86ddb40ab1747e3d9678f85ccbb0946aeffd8e29cd6a76134","cross_cats_sorted":["physics.flu-dyn"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-05-12T07:39:30Z","title_canon_sha256":"333b23f3471b50665e36830c5c4090005df9a83fefe51291f36a0972888aed6d"},"schema_version":"1.0","source":{"id":"2105.05482","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.05482","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"arxiv_version","alias_value":"2105.05482v1","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.05482","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_12","alias_value":"HATZ44FDX2TS","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_16","alias_value":"HATZ44FDX2TSQY6B","created_at":"2026-07-05T02:44:37Z"},{"alias_kind":"pith_short_8","alias_value":"HATZ44FD","created_at":"2026-07-05T02:44:37Z"}],"graph_snapshots":[{"event_id":"sha256:9b48e3c8ace78e654188e01f04be18fcaaac8825f625946f53d0f82a15231f72","target":"graph","created_at":"2026-07-05T02:44:37Z","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/2105.05482/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reproducibility of a deep-learning fully convolutional neural network is evaluated by training several times the same network on identical conditions (database, hyperparameters, hardware) with non-deterministic Graphics Processings Unit (GPU) operations. The propagation of two-dimensional acoustic waves, typical of time-space evolving physical systems, is studied on both recursive and non-recursive tasks. Significant changes in models properties (weights, featured fields) are observed. When tested on various propagation benchmarks, these models systematically returned estimations with a high l","authors_text":"Antonio Alguacil, Micha\\\"el Bauerheim, Wagner Gon\\c{c}alves Pinto","cross_cats":["physics.flu-dyn"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-05-12T07:39:30Z","title":"On the reproducibility of fully convolutional neural networks for modeling time-space evolving physical systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.05482","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":"sha256:0034c1b5ae7bd1520f078c94151bc1dc461e42d931efc41c0904e2045dcf8842","target":"record","created_at":"2026-07-05T02:44:37Z","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":"fe4499900bf43ba86ddb40ab1747e3d9678f85ccbb0946aeffd8e29cd6a76134","cross_cats_sorted":["physics.flu-dyn"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2021-05-12T07:39:30Z","title_canon_sha256":"333b23f3471b50665e36830c5c4090005df9a83fefe51291f36a0972888aed6d"},"schema_version":"1.0","source":{"id":"2105.05482","kind":"arxiv","version":1}},"canonical_sha256":"38279e70a3bea72863c1f64170c38c63ba3a96b2bcc345fc1e04d4e221c54a34","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"38279e70a3bea72863c1f64170c38c63ba3a96b2bcc345fc1e04d4e221c54a34","first_computed_at":"2026-07-05T02:44:37.480864Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:44:37.480864Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LnNj/rp7tE5J53GBalDXLmVH3FFGKte95LCoTzXcW9X+hhVYGSYbDfGdfW29Y2QYT62qwzNMP6I9FMR1oriUDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:44:37.481311Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.05482","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0034c1b5ae7bd1520f078c94151bc1dc461e42d931efc41c0904e2045dcf8842","sha256:9b48e3c8ace78e654188e01f04be18fcaaac8825f625946f53d0f82a15231f72"],"state_sha256":"f98876d51403485192dc336df5ea2714324fa437784e76797bcc0ecc2b4012fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2+HK5foTExwa3fdvxRWe7JbpLHUMThjBf5IRQ1Z8pHBEfzxjAH3CaH4/d/3bMq+zcMxc1cbk569500zhVNjtBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T18:37:00.932954Z","bundle_sha256":"906aa16927bb1fd5a4e01ac9c256665f774194ae3b370360091417b7d77ee544"}}