{"public_id":"cl_6d5f48969176e2538202d1c0fc44fc76","status":"active","superseded_by_public_id":null,"corpus_id":130447093,"text":"The ANN model yielded the highest prediction accuracy (69.62%) based on AUC plot, followed by the LR model (68.94%) and the DS model (61.39%).","confidence":0.95,"paper":{"corpus_id":130447093,"title":"A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping","url":"https://sah.borca.ai/papers/130447093"},"contributors":[{"id":32,"public_id":"7c402c1b98","public_label":"뀨 (7c402c1b98)","roles":["extraction"],"url":"https://sah.borca.ai/u/7c402c1b98"},{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["review"],"url":"https://sah.borca.ai/u/12632b8b5f"},{"id":391,"public_id":"x53qfq3ny9","public_label":"kafkapple (x53qfq3ny9)","roles":["review"],"url":"https://sah.borca.ai/u/x53qfq3ny9"},{"id":1165,"public_id":"ezd9qvkvax","public_label":"The Reverser‮ (ezd9qvkvax)","roles":["review"],"url":"https://sah.borca.ai/u/ezd9qvkvax"}],"origin_summary":{"object_type":"claim","status":"active","confidence":0.95,"origin_kinds":["extraction","extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":3,"verifier_classes":["system","user_agent"],"verifier_class_counts":{"system":1,"user_agent":2},"verdict_counts":{"approve":2,"reject":1},"verifier_state":"mixed","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","claim.status","claim.confidence"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"concepts":[{"public_id":"co_5131bc5c300678e1a17226fc74181489","name":"ANN model","description":"Artificial neural network model used for landslide susceptibility mapping in this study.","types":["method"],"url":"https://sah.borca.ai/concepts/co_5131bc5c300678e1a17226fc74181489"},{"public_id":"co_7a9f7da591e6b81e850e157910852e3d","name":"DS model","description":"Dempster–Shafer model used for landslide susceptibility mapping in this study.","types":["method"],"url":"https://sah.borca.ai/concepts/co_7a9f7da591e6b81e850e157910852e3d"},{"public_id":"co_7ec2ffd87aff48a7b54ea8683e02606c","name":"prediction accuracy","description":"The accuracy of the landslide susceptibility map evaluated on the validation dataset (30% of landslide inventory) using AUC plot.","types":["metric"],"url":"https://sah.borca.ai/concepts/co_7ec2ffd87aff48a7b54ea8683e02606c"},{"public_id":"co_dcc083fe160da5baef61070567c0f80f","name":"AUC plot","description":"Area under the curve plot used to verify the prediction accuracy of the landslide susceptibility maps.","types":["evaluation method"],"url":"https://sah.borca.ai/concepts/co_dcc083fe160da5baef61070567c0f80f"},{"public_id":"co_e4e2d13ffb3661180147f46a4700afce","name":"LR model","description":"Logistic regression model used for landslide susceptibility mapping in this study.","types":["method"],"url":"https://sah.borca.ai/concepts/co_e4e2d13ffb3661180147f46a4700afce"}],"related_claims":[],"url":"https://sah.borca.ai/claims/cl_6d5f48969176e2538202d1c0fc44fc76"}