{"id":"W3180986011","doi":"10.3390/ijgi10070461","title":"Assessing Earthquake Impacts and Monitoring Resilience of Historic Areas: Methods for GIS Tools","year":2021,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Circulatory and Respiratory Health; Horizon 2020; Università degli Studi di Camerino","keywords":"Damages; Resilience (materials science); Vulnerability (computing); Hazard; Natural hazard; Computer science; Vulnerability assessment; Environmental resource management; Geographic information system; Environmental science; Geography; Computer security; Remote sensing; Psychological resilience","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00243479,0.001058181,0.0005373898,0.005299075,0.0002425719,0.001680491,0.00106067,0.0005890797,0.002732827],"category_scores_gemma":[0.006876441,0.0004434361,0.0005552846,0.003466442,0.0009639187,0.001796388,0.001261717,0.0006196251,0.0006557051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000644966,"about_ca_system_score_gemma":0.0005680613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003308727,"about_ca_topic_score_gemma":0.002790409,"domain_scores_codex":[0.999065,0.000485153,0.00007747272,0.0001128616,0.0002278114,0.00003174953],"domain_scores_gemma":[0.9968298,0.002093674,0.0003120565,0.0003308505,0.0003331396,0.0001004738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001350879,0.0001453912,0.02387806,0.0006756159,0.0002509393,0.0002476468,0.001614506,0.2039063,0.00970261,0.06565265,0.005947265,0.687844],"study_design_scores_gemma":[0.00003317827,0.00008379031,0.0116991,0.0001840328,0.00007567463,0.000354856,0.001529607,0.872221,0.00748336,0.08488958,0.02135382,0.00009202003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007544734,0.000296806,0.9881732,0.0002168768,0.00001319391,0.00007380429,0.0004559985,0.001706911,0.001518524],"genre_scores_gemma":[0.1720755,0.0006518438,0.8252521,0.00004440769,0.00002671786,0.0003261119,0.0005237929,0.0001798362,0.0009197789],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005299075,"threshold_uncertainty_score":0.01287657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01546009219673659,"score_gpt":0.3384879528427809,"score_spread":0.3230278606460443,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}