{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","short_pith_number":"pith:TECX5WTE","canonical_record":{"source":{"id":"2607.18777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-21T06:59:25Z","cross_cats_sorted":["q-bio.MN"],"title_canon_sha256":"7993fa4c65045fafc6650d4f13109464d19eb6a1e3a977400623f5a91fb3f40d","abstract_canon_sha256":"eae82428ad8e5620aa007db789642c01111e0c1ee3e061d9120dd342f3513a33"},"schema_version":"1.0"},"canonical_sha256":"99057eda64711d6a28241e60400bf2378f5ae893af5ce81d86da54c94f907520","source":{"kind":"arxiv","id":"2607.18777","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18777","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18777v1","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18777","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_12","alias_value":"TECX5WTEOEOW","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_16","alias_value":"TECX5WTEOEOWUKBE","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_8","alias_value":"TECX5WTE","created_at":"2026-07-22T01:23:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","target":"record","payload":{"canonical_record":{"source":{"id":"2607.18777","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-21T06:59:25Z","cross_cats_sorted":["q-bio.MN"],"title_canon_sha256":"7993fa4c65045fafc6650d4f13109464d19eb6a1e3a977400623f5a91fb3f40d","abstract_canon_sha256":"eae82428ad8e5620aa007db789642c01111e0c1ee3e061d9120dd342f3513a33"},"schema_version":"1.0"},"canonical_sha256":"99057eda64711d6a28241e60400bf2378f5ae893af5ce81d86da54c94f907520","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-22T01:23:11.411872Z","signature_b64":"sTVxsPpYkfZxZ+rsCCBslatVkmlnu5xDkfg1Hxj/OIetJuAUF54X5XPB83Ee9KGWm6NUgor4hf8edfjqdgxnBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99057eda64711d6a28241e60400bf2378f5ae893af5ce81d86da54c94f907520","last_reissued_at":"2026-07-22T01:23:11.411061Z","signature_status":"signed_v1","first_computed_at":"2026-07-22T01:23:11.411061Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.18777","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":"2026-07-22T01:23:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pc+G6p4x77DEdpv/kQTUecpqZ31N22pkSlfFaestwm95O4KlpmTpaKxL54L4yC4E2l8+55+ZqR7r5/CnsdbSCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:26:55.147358Z"},"content_sha256":"ca09b7f66aba5a44222467577f89af1472e05d3d04f807ec04417ceb04de7ade","schema_version":"1.0","event_id":"sha256:ca09b7f66aba5a44222467577f89af1472e05d3d04f807ec04417ceb04de7ade"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PertReason: A Knowledge-Grounded Benchmark and Framework for Cell-State-Conditioned Mechanistic Reasoning of Perturbation Effects","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.MN"],"primary_cat":"cs.LG","authors_text":"Dongkwan Kim, Yang Shen, Yiming Gao, Yining Yang","submitted_at":"2026-07-21T06:59:25Z","abstract_excerpt":"Evaluating machine learning in scientific domains requires separating correct predictions from correct reasons under realistic distribution shifts. We introduce PertReason, a knowledge-grounded benchmark and framework suite for cell-state--conditioned reasoning about perturbation effects. At its core, PertReasonQA is a benchmark that tests whether models can generate mechanistically faithful explanations while remaining robust to complex shifts, such as new cells and unseen perturbations. PertReasonQA combines single-cell genetic and chemical perturbation data across multiple cellular contexts"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18777","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/2607.18777/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":"2026-07-22T01:23:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B4W7R3Fy/ipjw9sYXxwksYbaLRdUk4Z9L3CUlbWz79Ikf6x/bXhNECVZArr5GjnHZ8ImsaOAjbiYfVH/FREQAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:26:55.148333Z"},"content_sha256":"1862a345637a2659ffae5e94d3361c5efe901e3827e84d871b0f368c2ffa24e4","schema_version":"1.0","event_id":"sha256:1862a345637a2659ffae5e94d3361c5efe901e3827e84d871b0f368c2ffa24e4"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","target":"integrity","payload":{"note":"DOI is split by whitespace or line breaks in the printed bibliography. Reconstructed DOI 10.1093/bioinformatics/bty294 resolves to 'Modeling polypharmacy side effects with graph convolutional networks'. A reader following the printed text alone cannot reach it.","snippet":"Marinka Zitnik, Monica Agrawal, and Jure Leskovec. Modeling polypharmacy side effects with graph convolutional networks.Bioinformatics, 34(13):i457–i466, 06 2018. ISSN 1367-4803. doi: 10.1093/bioi nformatics/bty294. URLhttps://doi.org/10.10","arxiv_id":"2607.18777","detector":"doi_compliance","evidence":{"ref_index":61,"verdict_class":"incontrovertible","resolved_title":"Modeling polypharmacy side effects with graph convolutional networks","printed_excerpt":"10.1093/bioi","reconstructed_doi":"10.1093/bioinformatics/bty294"},"severity":"advisory","ref_index":61,"audited_at":"2026-08-01T14:39:36.108830Z","event_type":"pith.integrity.v1","detected_doi":"10.1093/bioinformatics/bty294","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"b5af0479fb6ca50b6273c16972cdff8601bde726dd88e693bab9083a69b7b934","paper_version":1,"verdict_class":"incontrovertible","resolved_title":"Modeling polypharmacy side effects with graph convolutional networks","detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":15970,"payload_sha256":"056ed2163001b19219d8c04eb749ae52626297d998a666da916d13c0f2f4a464","signature_b64":"Hc32HKkip235FLIo51ZorYBkhmZwCyhP9K9LBs7lkoGwmsTwLmFuoJAwlKIwuFRPGVZrwd915J4jXBo6FFsEAg==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-01T14:43:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q2zHtBSBPiybB7Go4eCoXfCSwL4BGz3IIRsdyeY0/etOtsD7489LAXaGfR/yqWsdvzp/4o9/83eYMlknMB/8Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:26:55.152767Z"},"content_sha256":"41743e3448d389cd10817c238a8388d3e99cc55e5589f6d5fb41be31560abd44","schema_version":"1.0","event_id":"sha256:41743e3448d389cd10817c238a8388d3e99cc55e5589f6d5fb41be31560abd44"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","target":"integrity","payload":{"note":"DOI is split by whitespace or line breaks in the printed bibliography. Reconstructed DOI 10.1093/bioinformatics/btt471 resolves to 'Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Ev'. A reader following the printed text alone cannot reach it.","snippet":"Evan O. Paull, Daniel E. Carlin, Mario Niepel, Peter K. Sorger, David Haussler, and Joshua M. Stuart. Discovering causal pathways linking genomic events to transcriptional states using tied diffusion through interacting events (tiedie).Bioi","arxiv_id":"2607.18777","detector":"doi_compliance","evidence":{"ref_index":30,"verdict_class":"incontrovertible","resolved_title":"Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Events (TieDIE)","printed_excerpt":"10.1093/bi","reconstructed_doi":"10.1093/bioinformatics/btt471"},"severity":"advisory","ref_index":30,"audited_at":"2026-08-01T14:39:36.108830Z","event_type":"pith.integrity.v1","detected_doi":"10.1093/bioinformatics/btt471","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"1ba8647468c58295f7e1a93b89d9077efe2a08d5e3bd6fff4a2c0a4db30128e3","paper_version":1,"verdict_class":"incontrovertible","resolved_title":"Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Events (TieDIE)","detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":15969,"payload_sha256":"036eed9b0bb7a9d4ee823a7128842027a1d10d58326483e917b22e769e5e0913","signature_b64":"acfxBgq/cCkGPzOoa71hqDM61hbGOsMXVtg4SbUSLQM0Bm8vX60sFPIQ4KOgeckAVSOmEKVGXbveun4JhNr2Ag==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-01T14:43:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3nEj4jdLgaG8ND1wnWkuqhpOub9XFXdUl3P/YwVZx1JSA9j8yK4mTpFNKqXx9K8Lr6pKx4ZlCbuk1an4hNREDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T07:26:55.153585Z"},"content_sha256":"3fd648debaed18d63ffd2440e0cd32ebb7ae5b5ebb0c70434f4660f0fcb12a59","schema_version":"1.0","event_id":"sha256:3fd648debaed18d63ffd2440e0cd32ebb7ae5b5ebb0c70434f4660f0fcb12a59"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/bundle.json","state_url":"https://pith.science/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/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":"2026-08-18T07:26:55Z","links":{"resolver":"https://pith.science/pith/TECX5WTEOEOWUKBEDZQEAC7SG6","bundle":"https://pith.science/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/bundle.json","state":"https://pith.science/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TECX5WTEOEOWUKBEDZQEAC7SG6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TECX5WTEOEOWUKBEDZQEAC7SG6","merge_version":"pith-open-graph-merge-v1","event_count":4,"valid_event_count":4,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"eae82428ad8e5620aa007db789642c01111e0c1ee3e061d9120dd342f3513a33","cross_cats_sorted":["q-bio.MN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-21T06:59:25Z","title_canon_sha256":"7993fa4c65045fafc6650d4f13109464d19eb6a1e3a977400623f5a91fb3f40d"},"schema_version":"1.0","source":{"id":"2607.18777","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18777","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18777v1","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18777","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_12","alias_value":"TECX5WTEOEOW","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_16","alias_value":"TECX5WTEOEOWUKBE","created_at":"2026-07-22T01:23:11Z"},{"alias_kind":"pith_short_8","alias_value":"TECX5WTE","created_at":"2026-07-22T01:23:11Z"}],"graph_snapshots":[{"event_id":"sha256:1862a345637a2659ffae5e94d3361c5efe901e3827e84d871b0f368c2ffa24e4","target":"graph","created_at":"2026-07-22T01:23:11Z","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/2607.18777/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Evaluating machine learning in scientific domains requires separating correct predictions from correct reasons under realistic distribution shifts. We introduce PertReason, a knowledge-grounded benchmark and framework suite for cell-state--conditioned reasoning about perturbation effects. At its core, PertReasonQA is a benchmark that tests whether models can generate mechanistically faithful explanations while remaining robust to complex shifts, such as new cells and unseen perturbations. PertReasonQA combines single-cell genetic and chemical perturbation data across multiple cellular contexts","authors_text":"Dongkwan Kim, Yang Shen, Yiming Gao, Yining Yang","cross_cats":["q-bio.MN"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-21T06:59:25Z","title":"PertReason: A Knowledge-Grounded Benchmark and Framework for Cell-State-Conditioned Mechanistic Reasoning of Perturbation Effects"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18777","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:ca09b7f66aba5a44222467577f89af1472e05d3d04f807ec04417ceb04de7ade","target":"record","created_at":"2026-07-22T01:23:11Z","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":"eae82428ad8e5620aa007db789642c01111e0c1ee3e061d9120dd342f3513a33","cross_cats_sorted":["q-bio.MN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-21T06:59:25Z","title_canon_sha256":"7993fa4c65045fafc6650d4f13109464d19eb6a1e3a977400623f5a91fb3f40d"},"schema_version":"1.0","source":{"id":"2607.18777","kind":"arxiv","version":1}},"canonical_sha256":"99057eda64711d6a28241e60400bf2378f5ae893af5ce81d86da54c94f907520","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99057eda64711d6a28241e60400bf2378f5ae893af5ce81d86da54c94f907520","first_computed_at":"2026-07-22T01:23:11.411061Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-22T01:23:11.411061Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sTVxsPpYkfZxZ+rsCCBslatVkmlnu5xDkfg1Hxj/OIetJuAUF54X5XPB83Ee9KGWm6NUgor4hf8edfjqdgxnBA==","signature_status":"signed_v1","signed_at":"2026-07-22T01:23:11.411872Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.18777","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:3fd648debaed18d63ffd2440e0cd32ebb7ae5b5ebb0c70434f4660f0fcb12a59","sha256:41743e3448d389cd10817c238a8388d3e99cc55e5589f6d5fb41be31560abd44"]}],"invalid_events":[],"applied_event_ids":["sha256:ca09b7f66aba5a44222467577f89af1472e05d3d04f807ec04417ceb04de7ade","sha256:1862a345637a2659ffae5e94d3361c5efe901e3827e84d871b0f368c2ffa24e4"],"state_sha256":"19544d99bac9e8066f7ca99159ce7739842b56725e80ee1a4731d197a25d2521"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IAOFgz+Yc6xYc27Vh5axz+BrdBm6UqNHpCYvNdILR3HYUZxPspbTC9jWl1Naz/yGK+fF+S8EyB/xWuNoXaCPBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T07:26:55.158482Z","bundle_sha256":"3145a30dc1e5f493c2b8e71fb869d907efa8b53c4df69c1bc876025d4b7c8ae2"}}