{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:UJ4SNR67PESP3KETXEE5TICVAW","short_pith_number":"pith:UJ4SNR67","canonical_record":{"source":{"id":"2509.09195","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-11T07:10:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"79559a3e5cbe7eef307330791ebc0e4f13b73b104eac073250d19da2399f3524","abstract_canon_sha256":"5e5b7ec2bf8b282f22e6e68bbf4815b3318f84a74beb6eb590f3e8bd91908356"},"schema_version":"1.0"},"canonical_sha256":"a27926c7df7924fda893b909d9a05505a0538b8b25c88f09a2cf68b869d27135","source":{"kind":"arxiv","id":"2509.09195","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09195","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09195v1","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09195","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_12","alias_value":"UJ4SNR67PESP","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_16","alias_value":"UJ4SNR67PESP3KET","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_8","alias_value":"UJ4SNR67","created_at":"2026-07-05T12:09:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:UJ4SNR67PESP3KETXEE5TICVAW","target":"record","payload":{"canonical_record":{"source":{"id":"2509.09195","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-11T07:10:45Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"79559a3e5cbe7eef307330791ebc0e4f13b73b104eac073250d19da2399f3524","abstract_canon_sha256":"5e5b7ec2bf8b282f22e6e68bbf4815b3318f84a74beb6eb590f3e8bd91908356"},"schema_version":"1.0"},"canonical_sha256":"a27926c7df7924fda893b909d9a05505a0538b8b25c88f09a2cf68b869d27135","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:31.411289Z","signature_b64":"r2AW8voK9SEyRWP0IwDzXYulQsnF6UcoEnRkEX07dGuo2KusUi+4SxJp3hEklIyOg+KK6rkjlrXpQUaSQy6YDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a27926c7df7924fda893b909d9a05505a0538b8b25c88f09a2cf68b869d27135","last_reissued_at":"2026-07-05T12:09:31.410761Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:31.410761Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.09195","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":"2026-07-05T12:09:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N1jX0E6woE7p3l6NBxMxl8ZVFqn+rUAyKi2TgJ0wmtUo64TBWZIq2nnFJaEogKZ3UQKJTu7Xuh262n3CweEMBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:21:48.928668Z"},"content_sha256":"e17b4d13596cde9a466d810c204e3ce13053e4e69df5862d4d115d1ca67a7130","schema_version":"1.0","event_id":"sha256:e17b4d13596cde9a466d810c204e3ce13053e4e69df5862d4d115d1ca67a7130"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:UJ4SNR67PESP3KETXEE5TICVAW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Breaking the Statistical Similarity Trap in Extreme Convection Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Md Tanveer Hossain Munim","submitted_at":"2025-09-11T07:10:45Z","abstract_excerpt":"Current evaluation metrics for deep learning weather models create a \"Statistical Similarity Trap\", rewarding blurry predictions while missing rare, high-impact events. We provide quantitative evidence of this trap, showing sophisticated baselines achieve 97.9% correlation yet 0.00 CSI for dangerous convection detection. We introduce DART (Dual Architecture for Regression Tasks), a framework addressing the challenge of transforming coarse atmospheric forecasts into high-resolution satellite brightness temperature fields optimized for extreme convection detection (below 220 K). DART employs dua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09195","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/2509.09195/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":"2026-07-05T12:09:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b+PpKwtGoVfUbUnVkqHq+EiJ22+6SpPn4dvCIvQ9FcleIp4tG7Lw3dP84GXWJjGKeiZb+30yXt7gPeZXJPiBCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T19:21:48.929191Z"},"content_sha256":"8aebe07477b3b19ed64627ae115b25a5e002f1d1028f6db79677c2dfae104e36","schema_version":"1.0","event_id":"sha256:8aebe07477b3b19ed64627ae115b25a5e002f1d1028f6db79677c2dfae104e36"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UJ4SNR67PESP3KETXEE5TICVAW/bundle.json","state_url":"https://pith.science/pith/UJ4SNR67PESP3KETXEE5TICVAW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UJ4SNR67PESP3KETXEE5TICVAW/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":"2026-08-08T19:21:48Z","links":{"resolver":"https://pith.science/pith/UJ4SNR67PESP3KETXEE5TICVAW","bundle":"https://pith.science/pith/UJ4SNR67PESP3KETXEE5TICVAW/bundle.json","state":"https://pith.science/pith/UJ4SNR67PESP3KETXEE5TICVAW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UJ4SNR67PESP3KETXEE5TICVAW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UJ4SNR67PESP3KETXEE5TICVAW","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":"5e5b7ec2bf8b282f22e6e68bbf4815b3318f84a74beb6eb590f3e8bd91908356","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-11T07:10:45Z","title_canon_sha256":"79559a3e5cbe7eef307330791ebc0e4f13b73b104eac073250d19da2399f3524"},"schema_version":"1.0","source":{"id":"2509.09195","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09195","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09195v1","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09195","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_12","alias_value":"UJ4SNR67PESP","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_16","alias_value":"UJ4SNR67PESP3KET","created_at":"2026-07-05T12:09:31Z"},{"alias_kind":"pith_short_8","alias_value":"UJ4SNR67","created_at":"2026-07-05T12:09:31Z"}],"graph_snapshots":[{"event_id":"sha256:8aebe07477b3b19ed64627ae115b25a5e002f1d1028f6db79677c2dfae104e36","target":"graph","created_at":"2026-07-05T12:09:31Z","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/2509.09195/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current evaluation metrics for deep learning weather models create a \"Statistical Similarity Trap\", rewarding blurry predictions while missing rare, high-impact events. We provide quantitative evidence of this trap, showing sophisticated baselines achieve 97.9% correlation yet 0.00 CSI for dangerous convection detection. We introduce DART (Dual Architecture for Regression Tasks), a framework addressing the challenge of transforming coarse atmospheric forecasts into high-resolution satellite brightness temperature fields optimized for extreme convection detection (below 220 K). DART employs dua","authors_text":"Md Tanveer Hossain Munim","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-11T07:10:45Z","title":"Breaking the Statistical Similarity Trap in Extreme Convection Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09195","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:e17b4d13596cde9a466d810c204e3ce13053e4e69df5862d4d115d1ca67a7130","target":"record","created_at":"2026-07-05T12:09:31Z","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":"5e5b7ec2bf8b282f22e6e68bbf4815b3318f84a74beb6eb590f3e8bd91908356","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-09-11T07:10:45Z","title_canon_sha256":"79559a3e5cbe7eef307330791ebc0e4f13b73b104eac073250d19da2399f3524"},"schema_version":"1.0","source":{"id":"2509.09195","kind":"arxiv","version":1}},"canonical_sha256":"a27926c7df7924fda893b909d9a05505a0538b8b25c88f09a2cf68b869d27135","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a27926c7df7924fda893b909d9a05505a0538b8b25c88f09a2cf68b869d27135","first_computed_at":"2026-07-05T12:09:31.410761Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:09:31.410761Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r2AW8voK9SEyRWP0IwDzXYulQsnF6UcoEnRkEX07dGuo2KusUi+4SxJp3hEklIyOg+KK6rkjlrXpQUaSQy6YDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:09:31.411289Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.09195","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e17b4d13596cde9a466d810c204e3ce13053e4e69df5862d4d115d1ca67a7130","sha256:8aebe07477b3b19ed64627ae115b25a5e002f1d1028f6db79677c2dfae104e36"],"state_sha256":"f196f9ece72e55e95bdb7561950999335a21b4119ccd6450c69b8f709b76d7d1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dtpVWC2U9viw1ClnXRCVlwkdtDR8xWkzG9i007WlIyC0Gn6P87+1slE8ynufnW5aX/vG4CtkcSmJi655koiDAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T19:21:48.935646Z","bundle_sha256":"b5d92b6dd76e253fc1b0c10529d2d8c7c15ef65c9cd6f8447a7286bf5704a0f3"}}