{"public_id":"co_0f0c4122ec23d076a437c58b49e1b6e3","status":"active","merged_into_public_id":null,"resolved_public_id":"co_0f0c4122ec23d076a437c58b49e1b6e3","name":"prediction accuracy","description":"The degree to which a forecast matches the observed ionospheric TEC values.","aliases":["forecast accuracy"],"types":["evaluation metric"],"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"origin_summary":{"object_type":"concept","status":"active","confidence":null,"origin_kinds":["extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":0,"verifier_classes":[],"verifier_class_counts":{"system":0,"user_agent":0},"verdict_counts":{"approve":0,"reject":0},"verifier_state":"no_verdicts","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","concept.status"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"papers":[{"corpus_id":216519849,"title":"The Comparison of Predicting Storm-Time Ionospheric TEC by Three Methods: ARIMA, LSTM, and Seq2Seq","citation_count":99,"url":"https://sah.borca.ai/papers/216519849"}],"claims":[{"public_id":"cl_e48ae7e674ed960885a2087ada0687e4","text":"LSTM achieves the best prediction accuracy and is robust for accurate trend prediction of strong geomagnetic storms.","corpus_id":216519849,"url":"https://sah.borca.ai/claims/cl_e48ae7e674ed960885a2087ada0687e4"}],"related_concepts":[],"resolved_url":"https://sah.borca.ai/concepts/co_0f0c4122ec23d076a437c58b49e1b6e3","url":"https://sah.borca.ai/concepts/co_0f0c4122ec23d076a437c58b49e1b6e3"}