{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:LJ4NKCMNCGEALHXZNOL675QSH2","short_pith_number":"pith:LJ4NKCMN","canonical_record":{"source":{"id":"2211.11227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T07:42:11Z","cross_cats_sorted":[],"title_canon_sha256":"adcfd4759677f9e399245376ad267bf6c1cd209a128d191165f300ed2ae16b3c","abstract_canon_sha256":"36abdfff7cc5cdfb206d868c1d8dab417c1ba1abdc4b8a6be87771acd2881f69"},"schema_version":"1.0"},"canonical_sha256":"5a78d5098d1188059ef96b97eff6123eb8989933767e36aaaf82ef55101ce4b4","source":{"kind":"arxiv","id":"2211.11227","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.11227","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2211.11227v1","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.11227","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"LJ4NKCMNCGEA","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"LJ4NKCMNCGEALHXZ","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"LJ4NKCMN","created_at":"2026-07-05T05:17:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:LJ4NKCMNCGEALHXZNOL675QSH2","target":"record","payload":{"canonical_record":{"source":{"id":"2211.11227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T07:42:11Z","cross_cats_sorted":[],"title_canon_sha256":"adcfd4759677f9e399245376ad267bf6c1cd209a128d191165f300ed2ae16b3c","abstract_canon_sha256":"36abdfff7cc5cdfb206d868c1d8dab417c1ba1abdc4b8a6be87771acd2881f69"},"schema_version":"1.0"},"canonical_sha256":"5a78d5098d1188059ef96b97eff6123eb8989933767e36aaaf82ef55101ce4b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:17:51.518638Z","signature_b64":"TLWkAO8YDms8paoKapUwdJbRPho1hKluVHm1rz1L6zABIZeA0hwAVoMAwHDnUZW2l/BRyvFYUv2xgfh4KLJ1BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5a78d5098d1188059ef96b97eff6123eb8989933767e36aaaf82ef55101ce4b4","last_reissued_at":"2026-07-05T05:17:51.518228Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:17:51.518228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.11227","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":"2026-07-05T05:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MK1u9kX9THhgltFsAy9hgC6JP41zgm5Z6oEFaRcu1O+vhnUO3FMpeC5Jd7zLg78fPN+WJB//CtmyiAhFWRyQAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T23:47:22.515034Z"},"content_sha256":"3cca347db3d94781931ccf966e2134c9a9ed45389dddf26b983340a083720d86","schema_version":"1.0","event_id":"sha256:3cca347db3d94781931ccf966e2134c9a9ed45389dddf26b983340a083720d86"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:LJ4NKCMNCGEALHXZNOL675QSH2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explainable Model-specific Algorithm Selection for Multi-Label Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ana Kostovska, Carola Doerr, Dragi Kocev, Pan\\v{c}e Panov, Sa\\v{s}o D\\v{z}eroski, Tome Eftimov","submitted_at":"2022-11-21T07:42:11Z","abstract_excerpt":"Multi-label classification (MLC) is an ML task of predictive modeling in which a data instance can simultaneously belong to multiple classes. MLC is increasingly gaining interest in different application domains such as text mining, computer vision, and bioinformatics. Several MLC algorithms have been proposed in the literature, resulting in a meta-optimization problem that the user needs to address: which MLC approach to select for a given dataset? To address this algorithm selection problem, we investigate in this work the quality of an automated approach that uses characteristics of the dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.11227","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/2211.11227/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":"2026-07-05T05:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eGfvnzF0zwEW9vLOJ5oWFh/IlaAmBAS/afr7s0gSW/g1DYNViZPaNHw5Wo36QiteLA6MiTXju73NdjNsv77LDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T23:47:22.515530Z"},"content_sha256":"6ce0074d43664b1573df4988e05aa7b90d053353fc0d422b546082e7b31b869b","schema_version":"1.0","event_id":"sha256:6ce0074d43664b1573df4988e05aa7b90d053353fc0d422b546082e7b31b869b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LJ4NKCMNCGEALHXZNOL675QSH2/bundle.json","state_url":"https://pith.science/pith/LJ4NKCMNCGEALHXZNOL675QSH2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LJ4NKCMNCGEALHXZNOL675QSH2/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":"2026-08-19T23:47:22Z","links":{"resolver":"https://pith.science/pith/LJ4NKCMNCGEALHXZNOL675QSH2","bundle":"https://pith.science/pith/LJ4NKCMNCGEALHXZNOL675QSH2/bundle.json","state":"https://pith.science/pith/LJ4NKCMNCGEALHXZNOL675QSH2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LJ4NKCMNCGEALHXZNOL675QSH2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LJ4NKCMNCGEALHXZNOL675QSH2","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":"36abdfff7cc5cdfb206d868c1d8dab417c1ba1abdc4b8a6be87771acd2881f69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T07:42:11Z","title_canon_sha256":"adcfd4759677f9e399245376ad267bf6c1cd209a128d191165f300ed2ae16b3c"},"schema_version":"1.0","source":{"id":"2211.11227","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.11227","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2211.11227v1","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.11227","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"LJ4NKCMNCGEA","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"LJ4NKCMNCGEALHXZ","created_at":"2026-07-05T05:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"LJ4NKCMN","created_at":"2026-07-05T05:17:51Z"}],"graph_snapshots":[{"event_id":"sha256:6ce0074d43664b1573df4988e05aa7b90d053353fc0d422b546082e7b31b869b","target":"graph","created_at":"2026-07-05T05:17:51Z","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/2211.11227/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-label classification (MLC) is an ML task of predictive modeling in which a data instance can simultaneously belong to multiple classes. MLC is increasingly gaining interest in different application domains such as text mining, computer vision, and bioinformatics. Several MLC algorithms have been proposed in the literature, resulting in a meta-optimization problem that the user needs to address: which MLC approach to select for a given dataset? To address this algorithm selection problem, we investigate in this work the quality of an automated approach that uses characteristics of the dat","authors_text":"Ana Kostovska, Carola Doerr, Dragi Kocev, Pan\\v{c}e Panov, Sa\\v{s}o D\\v{z}eroski, Tome Eftimov","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T07:42:11Z","title":"Explainable Model-specific Algorithm Selection for Multi-Label Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.11227","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":"sha256:3cca347db3d94781931ccf966e2134c9a9ed45389dddf26b983340a083720d86","target":"record","created_at":"2026-07-05T05:17:51Z","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":"36abdfff7cc5cdfb206d868c1d8dab417c1ba1abdc4b8a6be87771acd2881f69","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-11-21T07:42:11Z","title_canon_sha256":"adcfd4759677f9e399245376ad267bf6c1cd209a128d191165f300ed2ae16b3c"},"schema_version":"1.0","source":{"id":"2211.11227","kind":"arxiv","version":1}},"canonical_sha256":"5a78d5098d1188059ef96b97eff6123eb8989933767e36aaaf82ef55101ce4b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a78d5098d1188059ef96b97eff6123eb8989933767e36aaaf82ef55101ce4b4","first_computed_at":"2026-07-05T05:17:51.518228Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:17:51.518228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TLWkAO8YDms8paoKapUwdJbRPho1hKluVHm1rz1L6zABIZeA0hwAVoMAwHDnUZW2l/BRyvFYUv2xgfh4KLJ1BA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:17:51.518638Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.11227","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3cca347db3d94781931ccf966e2134c9a9ed45389dddf26b983340a083720d86","sha256:6ce0074d43664b1573df4988e05aa7b90d053353fc0d422b546082e7b31b869b"],"state_sha256":"e151ebcb19332d1b2243aefcf4fa88e68921ab297e1f970a4489c04d791d3b58"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NvNJgXz+kqCkiZtt3r14LR71nGkt8GK12OTaWyZ905KX4TPxvjYeMvKd83qKqp+qHnw1GJKxKQGV7gXqIZ47CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T23:47:22.520771Z","bundle_sha256":"57bf23891840fdb1985e76edcb3689c8ad3921d461cae0563c62877fc809a7a8"}}