{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6TWYVQBE3TCWNY4ROI6PBR6O6Y","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":"58d7406373dec74f3d380544f782e3c65d7130c108972b8abe4893645bba872a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T03:13:03Z","title_canon_sha256":"3e7e12147b9ef410fbe7bd5150586adcf8b6249141558b121fe7f3d55d470381"},"schema_version":"1.0","source":{"id":"2606.07686","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.07686","created_at":"2026-06-09T00:04:46Z"},{"alias_kind":"arxiv_version","alias_value":"2606.07686v1","created_at":"2026-06-09T00:04:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.07686","created_at":"2026-06-09T00:04:46Z"},{"alias_kind":"pith_short_12","alias_value":"6TWYVQBE3TCW","created_at":"2026-06-09T00:04:46Z"},{"alias_kind":"pith_short_16","alias_value":"6TWYVQBE3TCWNY4R","created_at":"2026-06-09T00:04:46Z"},{"alias_kind":"pith_short_8","alias_value":"6TWYVQBE","created_at":"2026-06-09T00:04:46Z"}],"graph_snapshots":[{"event_id":"sha256:c51e073ab931a661848bd6e117fb420ad70a60fb25c388b4a28581afbe11afa8","target":"graph","created_at":"2026-06-09T00:04:46Z","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/2606.07686/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods. Beyond equations, knowledge exists in other forms, such as text and network structure. While existing PINN-based approaches discover equation parameters from data, they rely solely on experimental measurements. We propose a new PINN framework that enriches parameter discovery by incorporating auxiliary knowledge sources. We instantiate our framework for microbiology, where generalised Lotka-Volterra (gLV) serves as a biological foundation for modelling microbial communit","authors_text":"Asela Hevapathige, Rajith Vidanaarachchi, Ravisha Rupasinghe, Sachith Seneviratne, Saman Halgamuge, Sen-Lin Tang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T03:13:03Z","title":"Knowledge-Inclusive Adaptive Physics-Informed Neural Network for Microbial Interaction Modelling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.07686","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":"sha256:5ff57a7a3a3b37d194356a6e52af3f01ee9beedf5bb9e8b0e4d63b7e0f7bd586","target":"record","created_at":"2026-06-09T00:04:46Z","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":"58d7406373dec74f3d380544f782e3c65d7130c108972b8abe4893645bba872a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-05T03:13:03Z","title_canon_sha256":"3e7e12147b9ef410fbe7bd5150586adcf8b6249141558b121fe7f3d55d470381"},"schema_version":"1.0","source":{"id":"2606.07686","kind":"arxiv","version":1}},"canonical_sha256":"f4ed8ac024dcc566e391723cf0c7cef626d0123183e91cc5589dfb78a0c3b869","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f4ed8ac024dcc566e391723cf0c7cef626d0123183e91cc5589dfb78a0c3b869","first_computed_at":"2026-06-09T00:04:46.823216Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T00:04:46.823216Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"q5QnFcpqfSthUVvoo3R2L+LBoDbnJ724M3F3r5Id2ZGdVs1tNT9BPvqVegDTcttF/tGqgLFGyHdk1STq8aqrDQ==","signature_status":"signed_v1","signed_at":"2026-06-09T00:04:46.823599Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.07686","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ff57a7a3a3b37d194356a6e52af3f01ee9beedf5bb9e8b0e4d63b7e0f7bd586","sha256:c51e073ab931a661848bd6e117fb420ad70a60fb25c388b4a28581afbe11afa8"],"state_sha256":"480c0a7b5d60881b178e4c2c238d2e048fed629d0c51c47ade458937fc2b1bf8"}