{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:6TR5LTKXFLRUQYI3BU7AUHPCZI","short_pith_number":"pith:6TR5LTKX","schema_version":"1.0","canonical_sha256":"f4e3d5cd572ae348611b0d3e0a1de2ca1db090aee6887ad7f2bc99f7ab264b98","source":{"kind":"arxiv","id":"2106.11057","version":1},"attestation_state":"computed","paper":{"title":"QuaPy: A Python-Based Framework for Quantification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani","submitted_at":"2021-06-18T13:57:11Z","abstract_excerpt":"QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via supervised learning, where a quantifier is a predictor that estimates the relative frequencies (a.k.a. prevalence values) of the classes of interest in a sample of unlabelled data. While quantification can be trivially performed by applying a standard classifier to each unlabelled data item and counting how many data items have been assigned to each class, it has been shown that this \"classify and count\" method is o"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2106.11057","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-06-18T13:57:11Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"45105ff6b9b787b6217f5ac440af8ef8e8e4d88e99e1822d00a55c0c7d97c692","abstract_canon_sha256":"fafff2ebabf322fcb6b5fd2b6f28b8e2f952561bd7169df1a32a0e99c4a3d202"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:50:56.389227Z","signature_b64":"tdDjneVs5dZGsRblO9FS8lDoYxSIhLZZxP5ZJhAo15eIqkoRLcpFa1sSMn86Z/0y6mSarZ4yIZnIzfIL++AcCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f4e3d5cd572ae348611b0d3e0a1de2ca1db090aee6887ad7f2bc99f7ab264b98","last_reissued_at":"2026-07-05T02:50:56.388798Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:50:56.388798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"QuaPy: A Python-Based Framework for Quantification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani","submitted_at":"2021-06-18T13:57:11Z","abstract_excerpt":"QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via supervised learning, where a quantifier is a predictor that estimates the relative frequencies (a.k.a. prevalence values) of the classes of interest in a sample of unlabelled data. While quantification can be trivially performed by applying a standard classifier to each unlabelled data item and counting how many data items have been assigned to each class, it has been shown that this \"classify and count\" method is o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.11057","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/2106.11057/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2106.11057","created_at":"2026-07-05T02:50:56.388856+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.11057v1","created_at":"2026-07-05T02:50:56.388856+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.11057","created_at":"2026-07-05T02:50:56.388856+00:00"},{"alias_kind":"pith_short_12","alias_value":"6TR5LTKXFLRU","created_at":"2026-07-05T02:50:56.388856+00:00"},{"alias_kind":"pith_short_16","alias_value":"6TR5LTKXFLRUQYI3","created_at":"2026-07-05T02:50:56.388856+00:00"},{"alias_kind":"pith_short_8","alias_value":"6TR5LTKX","created_at":"2026-07-05T02:50:56.388856+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI","json":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI.json","graph_json":"https://pith.science/api/pith-number/6TR5LTKXFLRUQYI3BU7AUHPCZI/graph.json","events_json":"https://pith.science/api/pith-number/6TR5LTKXFLRUQYI3BU7AUHPCZI/events.json","paper":"https://pith.science/paper/6TR5LTKX"},"agent_actions":{"view_html":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI","download_json":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI.json","view_paper":"https://pith.science/paper/6TR5LTKX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.11057&json=true","fetch_graph":"https://pith.science/api/pith-number/6TR5LTKXFLRUQYI3BU7AUHPCZI/graph.json","fetch_events":"https://pith.science/api/pith-number/6TR5LTKXFLRUQYI3BU7AUHPCZI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI/action/storage_attestation","attest_author":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI/action/author_attestation","sign_citation":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI/action/citation_signature","submit_replication":"https://pith.science/pith/6TR5LTKXFLRUQYI3BU7AUHPCZI/action/replication_record"}},"created_at":"2026-07-05T02:50:56.388856+00:00","updated_at":"2026-07-05T02:50:56.388856+00:00"}