{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TMDJPI7MA4JK2ZUQTO4Y7YXNK6","short_pith_number":"pith:TMDJPI7M","canonical_record":{"source":{"id":"2605.17148","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-05-16T20:45:36Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fc1e639a8930a17e6d5cc0eacc1f3a9ea5d291d3f9125c9e35ddee0624d00c26","abstract_canon_sha256":"96d4b5bd233ae2f9658a3125a70bc16cb43c7344eb97d8b66ebb57f62f63f2eb"},"schema_version":"1.0"},"canonical_sha256":"9b0697a3ec0712ad66909bb98fe2ed578e40c51cfdadbd2077c7da09d24b7954","source":{"kind":"arxiv","id":"2605.17148","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17148","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17148v1","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17148","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_12","alias_value":"TMDJPI7MA4JK","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_16","alias_value":"TMDJPI7MA4JK2ZUQ","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_8","alias_value":"TMDJPI7M","created_at":"2026-05-20T00:03:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TMDJPI7MA4JK2ZUQTO4Y7YXNK6","target":"record","payload":{"canonical_record":{"source":{"id":"2605.17148","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-05-16T20:45:36Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fc1e639a8930a17e6d5cc0eacc1f3a9ea5d291d3f9125c9e35ddee0624d00c26","abstract_canon_sha256":"96d4b5bd233ae2f9658a3125a70bc16cb43c7344eb97d8b66ebb57f62f63f2eb"},"schema_version":"1.0"},"canonical_sha256":"9b0697a3ec0712ad66909bb98fe2ed578e40c51cfdadbd2077c7da09d24b7954","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:03:42.176227Z","signature_b64":"44f/WW4VTiwYkyiJfAuAE7cpvSkfI2cZJWlik3WRgYmlQ3lyYey4k4++LDz5F2k0FHEbhQ/jqv0dOjQiIr3GDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9b0697a3ec0712ad66909bb98fe2ed578e40c51cfdadbd2077c7da09d24b7954","last_reissued_at":"2026-05-20T00:03:42.175353Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:03:42.175353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.17148","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":"2026-05-20T00:03:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sGeOa2zdJMn75U5UKrElxR2xeL0m6LNWf+cgnIha82mU2cgsm1NPWD54nhGKgWF0w5yPQ/m1HtZEne8ITaQ4Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T19:12:56.316132Z"},"content_sha256":"657c9df157909c44937adddb16bfdc527a8cd8cb4d4d387347dc8b3a0b27e88b","schema_version":"1.0","event_id":"sha256:657c9df157909c44937adddb16bfdc527a8cd8cb4d4d387347dc8b3a0b27e88b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TMDJPI7MA4JK2ZUQTO4Y7YXNK6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evolutionary Extreme Learning Machine of ab-initio Energy Landscapes for Crystal Structure Prediction using Manta Ray Optimization with Levy Flight","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.NE","authors_text":"Adrian Rubio-Solis","submitted_at":"2026-05-16T20:45:36Z","abstract_excerpt":"The Manta Ray Foraging Optimization algorithm (MRFO) has proven to be a powerful heuristic strategy in the optimal solution of a large number of engineering problems. In this paper, an improvement of MRFO with Levy Flight is suggested for the training of extreme learning machines (ELMs) whose basic model is a Single Layer Feedforward Network (SLFN). The proposed methodology that we called Evolutionary EELM-MRFO-LF for short is implemented to the prediction of unrelaxed and relaxed formation energy compounds relative to ground state crystal structure of pure components in binary systems. EELM-M"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17148","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/2605.17148/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T22:33:23.767457Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T22:01:58.001408Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"4f0dbbfb615f5b92ae82dece710d643ca03a7428b8b79aee6dae5c7f79b377d3"},"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":"2026-05-20T00:03:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AqwQe/qlhwOWiySxqF8zrdOfb3IiYvcPHL6EV+m+bmsf+nakMmb6I6FsTqRIE8lelHICo/lM0Hf+KobYkUJzCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T19:12:56.316996Z"},"content_sha256":"d5fc3cc8b77c6be1a5da612bd20e485695376834bdb75ea61958764fbf1c8f30","schema_version":"1.0","event_id":"sha256:d5fc3cc8b77c6be1a5da612bd20e485695376834bdb75ea61958764fbf1c8f30"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/bundle.json","state_url":"https://pith.science/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/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":"2026-06-09T19:12:56Z","links":{"resolver":"https://pith.science/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6","bundle":"https://pith.science/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/bundle.json","state":"https://pith.science/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TMDJPI7MA4JK2ZUQTO4Y7YXNK6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TMDJPI7MA4JK2ZUQTO4Y7YXNK6","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":"96d4b5bd233ae2f9658a3125a70bc16cb43c7344eb97d8b66ebb57f62f63f2eb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-05-16T20:45:36Z","title_canon_sha256":"fc1e639a8930a17e6d5cc0eacc1f3a9ea5d291d3f9125c9e35ddee0624d00c26"},"schema_version":"1.0","source":{"id":"2605.17148","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.17148","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"arxiv_version","alias_value":"2605.17148v1","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.17148","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_12","alias_value":"TMDJPI7MA4JK","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_16","alias_value":"TMDJPI7MA4JK2ZUQ","created_at":"2026-05-20T00:03:42Z"},{"alias_kind":"pith_short_8","alias_value":"TMDJPI7M","created_at":"2026-05-20T00:03:42Z"}],"graph_snapshots":[{"event_id":"sha256:d5fc3cc8b77c6be1a5da612bd20e485695376834bdb75ea61958764fbf1c8f30","target":"graph","created_at":"2026-05-20T00:03:42Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T22:33:23.767457Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T22:01:58.001408Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.17148/integrity.json","findings":[],"snapshot_sha256":"4f0dbbfb615f5b92ae82dece710d643ca03a7428b8b79aee6dae5c7f79b377d3","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Manta Ray Foraging Optimization algorithm (MRFO) has proven to be a powerful heuristic strategy in the optimal solution of a large number of engineering problems. In this paper, an improvement of MRFO with Levy Flight is suggested for the training of extreme learning machines (ELMs) whose basic model is a Single Layer Feedforward Network (SLFN). The proposed methodology that we called Evolutionary EELM-MRFO-LF for short is implemented to the prediction of unrelaxed and relaxed formation energy compounds relative to ground state crystal structure of pure components in binary systems. EELM-M","authors_text":"Adrian Rubio-Solis","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-05-16T20:45:36Z","title":"Evolutionary Extreme Learning Machine of ab-initio Energy Landscapes for Crystal Structure Prediction using Manta Ray Optimization with Levy Flight"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.17148","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":"sha256:657c9df157909c44937adddb16bfdc527a8cd8cb4d4d387347dc8b3a0b27e88b","target":"record","created_at":"2026-05-20T00:03:42Z","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":"96d4b5bd233ae2f9658a3125a70bc16cb43c7344eb97d8b66ebb57f62f63f2eb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2026-05-16T20:45:36Z","title_canon_sha256":"fc1e639a8930a17e6d5cc0eacc1f3a9ea5d291d3f9125c9e35ddee0624d00c26"},"schema_version":"1.0","source":{"id":"2605.17148","kind":"arxiv","version":1}},"canonical_sha256":"9b0697a3ec0712ad66909bb98fe2ed578e40c51cfdadbd2077c7da09d24b7954","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9b0697a3ec0712ad66909bb98fe2ed578e40c51cfdadbd2077c7da09d24b7954","first_computed_at":"2026-05-20T00:03:42.175353Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:03:42.175353Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"44f/WW4VTiwYkyiJfAuAE7cpvSkfI2cZJWlik3WRgYmlQ3lyYey4k4++LDz5F2k0FHEbhQ/jqv0dOjQiIr3GDA==","signature_status":"signed_v1","signed_at":"2026-05-20T00:03:42.176227Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.17148","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:657c9df157909c44937adddb16bfdc527a8cd8cb4d4d387347dc8b3a0b27e88b","sha256:d5fc3cc8b77c6be1a5da612bd20e485695376834bdb75ea61958764fbf1c8f30"],"state_sha256":"7aa7c933dca2f647af5547ab657905f5e00612edcfa90ab71b21abb9f4caa91d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qkBB/fxuFpmblEcy+sHu0AkD6bf4sz3H2e6CqC+2RKsmh4gksMHuTR0lFa3A3x2RpW4BBaChj0Mikjt8ISKNCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T19:12:56.321904Z","bundle_sha256":"54f90136d217543dafa930a37321d9a54d470e23b23ac3c84039c86dc9f32d6c"}}