{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:LHSAFTYFYKD5RKR3QB6ZI334XJ","short_pith_number":"pith:LHSAFTYF","canonical_record":{"source":{"id":"2312.03443","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-06T11:54:50Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4649ac6c50dc2e5d0b1c2e88ef2923a549a77f5be74309d2ba5c8ec0544d5324","abstract_canon_sha256":"ce17fedba2db732f692176c9c59b6a79210b73e6169407eaedb535d3cb81c600"},"schema_version":"1.0"},"canonical_sha256":"59e402cf05c287d8aa3b807d946f7cba51035d8e054ef918e20aff29af0f4a25","source":{"kind":"arxiv","id":"2312.03443","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.03443","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"arxiv_version","alias_value":"2312.03443v1","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.03443","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_12","alias_value":"LHSAFTYFYKD5","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_16","alias_value":"LHSAFTYFYKD5RKR3","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_8","alias_value":"LHSAFTYF","created_at":"2026-07-05T08:35:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:LHSAFTYFYKD5RKR3QB6ZI334XJ","target":"record","payload":{"canonical_record":{"source":{"id":"2312.03443","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-06T11:54:50Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4649ac6c50dc2e5d0b1c2e88ef2923a549a77f5be74309d2ba5c8ec0544d5324","abstract_canon_sha256":"ce17fedba2db732f692176c9c59b6a79210b73e6169407eaedb535d3cb81c600"},"schema_version":"1.0"},"canonical_sha256":"59e402cf05c287d8aa3b807d946f7cba51035d8e054ef918e20aff29af0f4a25","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:35:39.845750Z","signature_b64":"r73+IYzbw31bKBIoNIk/fpwWvnRCxt6Ub3q3xI3Nr1Lp7XIkfZw/boEBf44rJGdYTJOwq/+UesyC/W0M1OX2Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59e402cf05c287d8aa3b807d946f7cba51035d8e054ef918e20aff29af0f4a25","last_reissued_at":"2026-07-05T08:35:39.845279Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:35:39.845279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.03443","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":"2026-07-05T08:35:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U2Sv+wZx3SZVbys04f3O5CD4iUEwdScZdeCh/PSQaEAetg4gbwDdF1f+35FEo9UgLHD33g2x4rndXvxz3l4aAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:29:23.314114Z"},"content_sha256":"0c20c12b8532e918f941bc1230ff7d4744ab0297bda306dfc55a49c4bcb51faa","schema_version":"1.0","event_id":"sha256:0c20c12b8532e918f941bc1230ff7d4744ab0297bda306dfc55a49c4bcb51faa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:LHSAFTYFYKD5RKR3QB6ZI334XJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.CV","authors_text":"Dereje T. Demie, Johannes Leonhardt, Lukas Drees, Madhuri R. Paul, Ribana Roscher, Sabine J. Seidel, Thomas F. D\\\"oring","submitted_at":"2023-12-06T11:54:50Z","abstract_excerpt":"Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. We present a two-stage framework consisting first of an image prediction model and secon"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.03443","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/2312.03443/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":"2026-07-05T08:35:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RIczN4R222D5v59H/cfSMdRWw/xpdcPyQfKWgtX5juYU8s/0SpuBfjOwQS0n5TysakKS3jD3Kfm43vJaFrFoCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:29:23.314620Z"},"content_sha256":"72c67a744f3ad521dc92fa439f1a89832b74341cfb35cc6c4a0224589ff5a243","schema_version":"1.0","event_id":"sha256:72c67a744f3ad521dc92fa439f1a89832b74341cfb35cc6c4a0224589ff5a243"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/bundle.json","state_url":"https://pith.science/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/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":"2026-08-07T00:29:23Z","links":{"resolver":"https://pith.science/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ","bundle":"https://pith.science/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/bundle.json","state":"https://pith.science/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LHSAFTYFYKD5RKR3QB6ZI334XJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LHSAFTYFYKD5RKR3QB6ZI334XJ","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":"ce17fedba2db732f692176c9c59b6a79210b73e6169407eaedb535d3cb81c600","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-06T11:54:50Z","title_canon_sha256":"4649ac6c50dc2e5d0b1c2e88ef2923a549a77f5be74309d2ba5c8ec0544d5324"},"schema_version":"1.0","source":{"id":"2312.03443","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.03443","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"arxiv_version","alias_value":"2312.03443v1","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.03443","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_12","alias_value":"LHSAFTYFYKD5","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_16","alias_value":"LHSAFTYFYKD5RKR3","created_at":"2026-07-05T08:35:39Z"},{"alias_kind":"pith_short_8","alias_value":"LHSAFTYF","created_at":"2026-07-05T08:35:39Z"}],"graph_snapshots":[{"event_id":"sha256:72c67a744f3ad521dc92fa439f1a89832b74341cfb35cc6c4a0224589ff5a243","target":"graph","created_at":"2026-07-05T08:35:39Z","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/2312.03443/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. We present a two-stage framework consisting first of an image prediction model and secon","authors_text":"Dereje T. Demie, Johannes Leonhardt, Lukas Drees, Madhuri R. Paul, Ribana Roscher, Sabine J. Seidel, Thomas F. D\\\"oring","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-06T11:54:50Z","title":"Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.03443","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":"sha256:0c20c12b8532e918f941bc1230ff7d4744ab0297bda306dfc55a49c4bcb51faa","target":"record","created_at":"2026-07-05T08:35:39Z","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":"ce17fedba2db732f692176c9c59b6a79210b73e6169407eaedb535d3cb81c600","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-06T11:54:50Z","title_canon_sha256":"4649ac6c50dc2e5d0b1c2e88ef2923a549a77f5be74309d2ba5c8ec0544d5324"},"schema_version":"1.0","source":{"id":"2312.03443","kind":"arxiv","version":1}},"canonical_sha256":"59e402cf05c287d8aa3b807d946f7cba51035d8e054ef918e20aff29af0f4a25","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59e402cf05c287d8aa3b807d946f7cba51035d8e054ef918e20aff29af0f4a25","first_computed_at":"2026-07-05T08:35:39.845279Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:39.845279Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r73+IYzbw31bKBIoNIk/fpwWvnRCxt6Ub3q3xI3Nr1Lp7XIkfZw/boEBf44rJGdYTJOwq/+UesyC/W0M1OX2Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:39.845750Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.03443","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c20c12b8532e918f941bc1230ff7d4744ab0297bda306dfc55a49c4bcb51faa","sha256:72c67a744f3ad521dc92fa439f1a89832b74341cfb35cc6c4a0224589ff5a243"],"state_sha256":"7d00e30a5711f58b188c94ee5ed3d554d7ead2da8efc1d454bec555bebf5a79d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xEFGdzYiAzS6gknyMbN9VAo/rxYAeJbFz/I7/CJM3EFK0FFSO6U8uaVEZ4b9rRPsD//M2IKOj7200C1vc13EDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T00:29:23.319381Z","bundle_sha256":"7c14130e5bdf4a092351ec758f7765370f2e9fdfe9a9e7eda72743e77b5b12a2"}}