{"public_id":"co_89ebbd81387cd3e735260acd5e19ab0d","status":"active","merged_into_public_id":null,"resolved_public_id":"co_89ebbd81387cd3e735260acd5e19ab0d","name":"adaptive method","description":"A method that can adjust its representation or parameters to the problem at hand.","aliases":[],"types":["method property"],"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":2988078,"title":"The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems","citation_count":1698,"url":"https://sah.borca.ai/papers/2988078"}],"claims":[],"related_concepts":[],"resolved_url":"https://sah.borca.ai/concepts/co_89ebbd81387cd3e735260acd5e19ab0d","url":"https://sah.borca.ai/concepts/co_89ebbd81387cd3e735260acd5e19ab0d"}