{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:HF5N2UL4TDCGMORXEMAPXLBX23","short_pith_number":"pith:HF5N2UL4","canonical_record":{"source":{"id":"2606.25769","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:45:17Z","cross_cats_sorted":[],"title_canon_sha256":"7aae66db4f0ca1b97c88e3dd6e9f0e343358a362f629fa714becd9012c92641d","abstract_canon_sha256":"4cfc0e1b87fb0d90ee8de2566be9fe77835a54069e4aee033392e0273210195e"},"schema_version":"1.0"},"canonical_sha256":"397add517c98c4663a372300fbac37d6dfc46aeaa5fc8ca31efd04bebc671f35","source":{"kind":"arxiv","id":"2606.25769","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25769","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25769v1","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25769","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_12","alias_value":"HF5N2UL4TDCG","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_16","alias_value":"HF5N2UL4TDCGMORX","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_8","alias_value":"HF5N2UL4","created_at":"2026-06-25T01:18:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:HF5N2UL4TDCGMORXEMAPXLBX23","target":"record","payload":{"canonical_record":{"source":{"id":"2606.25769","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:45:17Z","cross_cats_sorted":[],"title_canon_sha256":"7aae66db4f0ca1b97c88e3dd6e9f0e343358a362f629fa714becd9012c92641d","abstract_canon_sha256":"4cfc0e1b87fb0d90ee8de2566be9fe77835a54069e4aee033392e0273210195e"},"schema_version":"1.0"},"canonical_sha256":"397add517c98c4663a372300fbac37d6dfc46aeaa5fc8ca31efd04bebc671f35","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:14.775848Z","signature_b64":"MzBMLn5Si2szDPYcT+zlYhRH9NsDGItMNKI+Jxl9NxKItV0kfMvN6oEOm4SBhJB1KWdkttfejKmVEZxZwrstAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"397add517c98c4663a372300fbac37d6dfc46aeaa5fc8ca31efd04bebc671f35","last_reissued_at":"2026-06-25T01:18:14.775504Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:14.775504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.25769","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":"2026-06-25T01:18:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aplqR9qSsDHUpoIJRuGzJHsnkuW4W4PR2zakf9N9c0ALOSfGoy3EtfvnX0wVZC6Dwk5pe/+q2/busPqs99pfBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T07:30:18.456238Z"},"content_sha256":"9f1926509ebc9f123a1b59de62f335dea5ae999fa0c21c3801021e6fdec40dec","schema_version":"1.0","event_id":"sha256:9f1926509ebc9f123a1b59de62f335dea5ae999fa0c21c3801021e6fdec40dec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:HF5N2UL4TDCGMORXEMAPXLBX23","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Neural Networks with Ordinal Loss for Medical Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Gonen Singer, Rotem Haba, Tal Dvora","submitted_at":"2026-06-24T12:45:17Z","abstract_excerpt":"In many prediction problems in medical applications, target labels exhibit an inherent ordinal structure, where class ordering reflects clinically meaningful severity levels. The cost associated with misclassification is often non-uniform and asymmetric, as errors between distant ordinal categories may have substantially more severe consequences than errors between adjacent ones, and overestimating disease severity may have different clinical implications than underestimating it. Traditional loss functions such as multi-class cross-entropy treat all misclassifications equally and fail to incor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25769","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/2606.25769/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":"2026-06-25T01:18:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZOsXIlf5/JkA0/ztvHecfq26pcQG++xW9yHw6kdTwEvaJXa8z66uRsxB0GtKWI189JBJPdnyh36z5+38pOfzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T07:30:18.456617Z"},"content_sha256":"f6753803b736875569994baa9cc06b8db5f542c67d4584950a5202fa1656b5db","schema_version":"1.0","event_id":"sha256:f6753803b736875569994baa9cc06b8db5f542c67d4584950a5202fa1656b5db"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HF5N2UL4TDCGMORXEMAPXLBX23/bundle.json","state_url":"https://pith.science/pith/HF5N2UL4TDCGMORXEMAPXLBX23/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HF5N2UL4TDCGMORXEMAPXLBX23/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":"2026-07-05T07:30:18Z","links":{"resolver":"https://pith.science/pith/HF5N2UL4TDCGMORXEMAPXLBX23","bundle":"https://pith.science/pith/HF5N2UL4TDCGMORXEMAPXLBX23/bundle.json","state":"https://pith.science/pith/HF5N2UL4TDCGMORXEMAPXLBX23/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HF5N2UL4TDCGMORXEMAPXLBX23/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HF5N2UL4TDCGMORXEMAPXLBX23","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":"4cfc0e1b87fb0d90ee8de2566be9fe77835a54069e4aee033392e0273210195e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:45:17Z","title_canon_sha256":"7aae66db4f0ca1b97c88e3dd6e9f0e343358a362f629fa714becd9012c92641d"},"schema_version":"1.0","source":{"id":"2606.25769","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25769","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25769v1","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25769","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_12","alias_value":"HF5N2UL4TDCG","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_16","alias_value":"HF5N2UL4TDCGMORX","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_8","alias_value":"HF5N2UL4","created_at":"2026-06-25T01:18:14Z"}],"graph_snapshots":[{"event_id":"sha256:f6753803b736875569994baa9cc06b8db5f542c67d4584950a5202fa1656b5db","target":"graph","created_at":"2026-06-25T01:18:14Z","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/2606.25769/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In many prediction problems in medical applications, target labels exhibit an inherent ordinal structure, where class ordering reflects clinically meaningful severity levels. The cost associated with misclassification is often non-uniform and asymmetric, as errors between distant ordinal categories may have substantially more severe consequences than errors between adjacent ones, and overestimating disease severity may have different clinical implications than underestimating it. Traditional loss functions such as multi-class cross-entropy treat all misclassifications equally and fail to incor","authors_text":"Gonen Singer, Rotem Haba, Tal Dvora","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:45:17Z","title":"Deep Neural Networks with Ordinal Loss for Medical Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25769","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":"sha256:9f1926509ebc9f123a1b59de62f335dea5ae999fa0c21c3801021e6fdec40dec","target":"record","created_at":"2026-06-25T01:18:14Z","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":"4cfc0e1b87fb0d90ee8de2566be9fe77835a54069e4aee033392e0273210195e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:45:17Z","title_canon_sha256":"7aae66db4f0ca1b97c88e3dd6e9f0e343358a362f629fa714becd9012c92641d"},"schema_version":"1.0","source":{"id":"2606.25769","kind":"arxiv","version":1}},"canonical_sha256":"397add517c98c4663a372300fbac37d6dfc46aeaa5fc8ca31efd04bebc671f35","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"397add517c98c4663a372300fbac37d6dfc46aeaa5fc8ca31efd04bebc671f35","first_computed_at":"2026-06-25T01:18:14.775504Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:18:14.775504Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MzBMLn5Si2szDPYcT+zlYhRH9NsDGItMNKI+Jxl9NxKItV0kfMvN6oEOm4SBhJB1KWdkttfejKmVEZxZwrstAw==","signature_status":"signed_v1","signed_at":"2026-06-25T01:18:14.775848Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25769","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f1926509ebc9f123a1b59de62f335dea5ae999fa0c21c3801021e6fdec40dec","sha256:f6753803b736875569994baa9cc06b8db5f542c67d4584950a5202fa1656b5db"],"state_sha256":"034778bf26209c47e528386a9cdb0bbd123cbbb38fec486b504d44b92e3b96b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0dXE/UHhtmYk0hD4mi5hplhOSaGXVCrD3QDW5493xDLYS8aU2F5Cn2RVYlgexW7+iS92vpLCHlN5xozHzGRsDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T07:30:18.458618Z","bundle_sha256":"7da63351038f8582ac586a31f6968668fd9f121f114225dbe8df8f1f902dfb2f"}}