{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2009:JJVJPON2PHW2B767FZVJ5VXAJ4","short_pith_number":"pith:JJVJPON2","canonical_record":{"source":{"id":"0910.0949","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-10-06T08:47:29Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"0de30759feaa5aa48ddd8e10f14e426638565a0c26326766cba69b1f84a40ffe","abstract_canon_sha256":"b1ef5c60a5041de835ca333d8d379b234b195777c29e7712be0fefdf2fa20b4c"},"schema_version":"1.0"},"canonical_sha256":"4a6a97b9ba79eda0ffdf2e6a9ed6e04f1fe450caa7a59bcfe02298d8a9512284","source":{"kind":"arxiv","id":"0910.0949","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0910.0949","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"arxiv_version","alias_value":"0910.0949v1","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0910.0949","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"pith_short_12","alias_value":"JJVJPON2PHW2","created_at":"2026-05-18T12:26:00Z"},{"alias_kind":"pith_short_16","alias_value":"JJVJPON2PHW2B767","created_at":"2026-05-18T12:26:00Z"},{"alias_kind":"pith_short_8","alias_value":"JJVJPON2","created_at":"2026-05-18T12:26:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2009:JJVJPON2PHW2B767FZVJ5VXAJ4","target":"record","payload":{"canonical_record":{"source":{"id":"0910.0949","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-10-06T08:47:29Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"0de30759feaa5aa48ddd8e10f14e426638565a0c26326766cba69b1f84a40ffe","abstract_canon_sha256":"b1ef5c60a5041de835ca333d8d379b234b195777c29e7712be0fefdf2fa20b4c"},"schema_version":"1.0"},"canonical_sha256":"4a6a97b9ba79eda0ffdf2e6a9ed6e04f1fe450caa7a59bcfe02298d8a9512284","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:59.702139Z","signature_b64":"Gvm4tZimtHMtI282h25qmNxxlUqID2BfHxFqjWTOc/NwbD+jeG21GvgVaIXdi0rmUlkgbLx+SJFffEAZLzOfCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4a6a97b9ba79eda0ffdf2e6a9ed6e04f1fe450caa7a59bcfe02298d8a9512284","last_reissued_at":"2026-05-18T01:04:59.701687Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:59.701687Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"0910.0949","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":"2026-05-18T01:04:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y0WXQahRanqioVwMq5T88vu+YUqAGNr+k/x1gCMMH5gr6ganlSg0gZqKKMLfRG/QamUQo5bTYauLTSUzBZUCCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T16:38:12.363519Z"},"content_sha256":"4f6229e6974664a176915f7c1daf4b1b5c0befa3b4e131cc1bbf650cbd7e75da","schema_version":"1.0","event_id":"sha256:4f6229e6974664a176915f7c1daf4b1b5c0befa3b4e131cc1bbf650cbd7e75da"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2009:JJVJPON2PHW2B767FZVJ5VXAJ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BRAINSTORMING: Consensus Learning in Practice","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"stat.ML","authors_text":"02-106 Warsaw, Computational Modelling, Dariusz Plewczynski (ICM, Interdisciplinary Centre for Mathematical, Pawinskiego 5a Street, Poland), University of Warsaw","submitted_at":"2009-10-06T08:47:29Z","abstract_excerpt":"We present here an introduction to Brainstorming approach, that was recently proposed as a consensus meta-learning technique, and used in several practical applications in bioinformatics and chemoinformatics. The consensus learning denotes heterogeneous theoretical classification method, where one trains an ensemble of machine learning algorithms using different types of input training data representations. In the second step all solutions are gathered and the consensus is build between them. Therefore no early solution, given even by a generally low performing algorithm, is not discarder unti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0910.0949","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":""},"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":"2026-05-18T01:04:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qUuOvNP0qEMnao2Q98l28RE4Sp/9+NLfAuEnTbFUlNbgofRieLgHk7endRs4TPm8iB4wc0x5REJcRbWShc2YBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T16:38:12.363871Z"},"content_sha256":"290435dd53dacda03a12baf47017ef98f2f74c8d1a5aefe15ba2eb965e2582a1","schema_version":"1.0","event_id":"sha256:290435dd53dacda03a12baf47017ef98f2f74c8d1a5aefe15ba2eb965e2582a1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/bundle.json","state_url":"https://pith.science/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/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":"2026-05-28T16:38:12Z","links":{"resolver":"https://pith.science/pith/JJVJPON2PHW2B767FZVJ5VXAJ4","bundle":"https://pith.science/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/bundle.json","state":"https://pith.science/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JJVJPON2PHW2B767FZVJ5VXAJ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2009:JJVJPON2PHW2B767FZVJ5VXAJ4","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":"b1ef5c60a5041de835ca333d8d379b234b195777c29e7712be0fefdf2fa20b4c","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-10-06T08:47:29Z","title_canon_sha256":"0de30759feaa5aa48ddd8e10f14e426638565a0c26326766cba69b1f84a40ffe"},"schema_version":"1.0","source":{"id":"0910.0949","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"0910.0949","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"arxiv_version","alias_value":"0910.0949v1","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.0910.0949","created_at":"2026-05-18T01:04:59Z"},{"alias_kind":"pith_short_12","alias_value":"JJVJPON2PHW2","created_at":"2026-05-18T12:26:00Z"},{"alias_kind":"pith_short_16","alias_value":"JJVJPON2PHW2B767","created_at":"2026-05-18T12:26:00Z"},{"alias_kind":"pith_short_8","alias_value":"JJVJPON2","created_at":"2026-05-18T12:26:00Z"}],"graph_snapshots":[{"event_id":"sha256:290435dd53dacda03a12baf47017ef98f2f74c8d1a5aefe15ba2eb965e2582a1","target":"graph","created_at":"2026-05-18T01:04:59Z","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"},"paper":{"abstract_excerpt":"We present here an introduction to Brainstorming approach, that was recently proposed as a consensus meta-learning technique, and used in several practical applications in bioinformatics and chemoinformatics. The consensus learning denotes heterogeneous theoretical classification method, where one trains an ensemble of machine learning algorithms using different types of input training data representations. In the second step all solutions are gathered and the consensus is build between them. Therefore no early solution, given even by a generally low performing algorithm, is not discarder unti","authors_text":"02-106 Warsaw, Computational Modelling, Dariusz Plewczynski (ICM, Interdisciplinary Centre for Mathematical, Pawinskiego 5a Street, Poland), University of Warsaw","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-10-06T08:47:29Z","title":"BRAINSTORMING: Consensus Learning in Practice"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"0910.0949","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":"sha256:4f6229e6974664a176915f7c1daf4b1b5c0befa3b4e131cc1bbf650cbd7e75da","target":"record","created_at":"2026-05-18T01:04:59Z","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":"b1ef5c60a5041de835ca333d8d379b234b195777c29e7712be0fefdf2fa20b4c","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2009-10-06T08:47:29Z","title_canon_sha256":"0de30759feaa5aa48ddd8e10f14e426638565a0c26326766cba69b1f84a40ffe"},"schema_version":"1.0","source":{"id":"0910.0949","kind":"arxiv","version":1}},"canonical_sha256":"4a6a97b9ba79eda0ffdf2e6a9ed6e04f1fe450caa7a59bcfe02298d8a9512284","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4a6a97b9ba79eda0ffdf2e6a9ed6e04f1fe450caa7a59bcfe02298d8a9512284","first_computed_at":"2026-05-18T01:04:59.701687Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:04:59.701687Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Gvm4tZimtHMtI282h25qmNxxlUqID2BfHxFqjWTOc/NwbD+jeG21GvgVaIXdi0rmUlkgbLx+SJFffEAZLzOfCw==","signature_status":"signed_v1","signed_at":"2026-05-18T01:04:59.702139Z","signed_message":"canonical_sha256_bytes"},"source_id":"0910.0949","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4f6229e6974664a176915f7c1daf4b1b5c0befa3b4e131cc1bbf650cbd7e75da","sha256:290435dd53dacda03a12baf47017ef98f2f74c8d1a5aefe15ba2eb965e2582a1"],"state_sha256":"abc83d6d8862758c87aa1d1fd30856618412389d86b25866d6b7c984024c2b14"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xlXIWYokR7fs+5lp8d0JWnye4LmrFr0o4ChE8klxhPGe3iAPiel1akARolfGJYQrStnYcZofYAcyux7LhywUCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T16:38:12.366037Z","bundle_sha256":"ce2222688cd7973c8cf4ae7ea40d1be2c656fd465ef4d93f4ad65eee880341cf"}}