{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:WRMJDL6PC5SWGNSP2E3DW6JTB7","short_pith_number":"pith:WRMJDL6P","schema_version":"1.0","canonical_sha256":"b45891afcf176563364fd1363b79330fc45d783cb1f5e30644f976e37f9650bb","source":{"kind":"arxiv","id":"1809.10632","version":2},"attestation_state":"computed","paper":{"title":"Scalable visualisation methods for modern Generalized Additive Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Matteo Fasiolo, Rapha\\\"el Nedellec, Simon N. Wood, Yannig Goude","submitted_at":"2018-09-27T16:51:33Z","abstract_excerpt":"In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been matched by improved visualisations for model development and results presentation. Motivated by an industrial application in electricity load forecasting, we identify the areas where the lack of modern visualisation tools for GAMs is particularly severe, and we address the shortcomings of existing methods by proposing a set of visual tools that a) are fast enou"},"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":"1809.10632","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2018-09-27T16:51:33Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"a4e529dc8773af844e12b8a7d0f6acadb1fa435fae74ecbb6e7b47a6d7e418f4","abstract_canon_sha256":"d135caf60537ea47ef0f6140531621e7894b8c518942bc47c9150a52da4378b6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:41.589550Z","signature_b64":"7uhr5isRwD/ZFr8rBcZAsWBcbGzFD0PG+Ah1mfGw/JBXCqLEwpOWx3C9BaC5KfPFqVbyzt3YvZT+t8qqQjEwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b45891afcf176563364fd1363b79330fc45d783cb1f5e30644f976e37f9650bb","last_reissued_at":"2026-05-17T23:46:41.588919Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:41.588919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Scalable visualisation methods for modern Generalized Additive Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Matteo Fasiolo, Rapha\\\"el Nedellec, Simon N. Wood, Yannig Goude","submitted_at":"2018-09-27T16:51:33Z","abstract_excerpt":"In the last two decades the growth of computational resources has made it possible to handle Generalized Additive Models (GAMs) that formerly were too costly for serious applications. However, the growth in model complexity has not been matched by improved visualisations for model development and results presentation. Motivated by an industrial application in electricity load forecasting, we identify the areas where the lack of modern visualisation tools for GAMs is particularly severe, and we address the shortcomings of existing methods by proposing a set of visual tools that a) are fast enou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.10632","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1809.10632","created_at":"2026-05-17T23:46:41.589015+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.10632v2","created_at":"2026-05-17T23:46:41.589015+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.10632","created_at":"2026-05-17T23:46:41.589015+00:00"},{"alias_kind":"pith_short_12","alias_value":"WRMJDL6PC5SW","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"WRMJDL6PC5SWGNSP","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"WRMJDL6P","created_at":"2026-05-18T12:33:01.666342+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/WRMJDL6PC5SWGNSP2E3DW6JTB7","json":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7.json","graph_json":"https://pith.science/api/pith-number/WRMJDL6PC5SWGNSP2E3DW6JTB7/graph.json","events_json":"https://pith.science/api/pith-number/WRMJDL6PC5SWGNSP2E3DW6JTB7/events.json","paper":"https://pith.science/paper/WRMJDL6P"},"agent_actions":{"view_html":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7","download_json":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7.json","view_paper":"https://pith.science/paper/WRMJDL6P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.10632&json=true","fetch_graph":"https://pith.science/api/pith-number/WRMJDL6PC5SWGNSP2E3DW6JTB7/graph.json","fetch_events":"https://pith.science/api/pith-number/WRMJDL6PC5SWGNSP2E3DW6JTB7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7/action/storage_attestation","attest_author":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7/action/author_attestation","sign_citation":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7/action/citation_signature","submit_replication":"https://pith.science/pith/WRMJDL6PC5SWGNSP2E3DW6JTB7/action/replication_record"}},"created_at":"2026-05-17T23:46:41.589015+00:00","updated_at":"2026-05-17T23:46:41.589015+00:00"}