{"id":"W7115683381","doi":"10.71846/18-wcee-1542","title":"IS GEM (GLOBAL EARTHQUAKE MODEL) MAKING A DIFFERENCE?","year":2025,"lang":"en","type":"article","venue":"World Conference of Earthquake Engineering","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Resilience (materials science); Hazard; Government (linguistics); Risk assessment; Flood myth; Earthquake scenario; Emergency management; Urban seismic risk; Foundation (evidence)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01177038,0.001271722,0.001053079,0.00156415,0.0007907791,0.006751833,0.003637295,0.004875589,0.02004709],"category_scores_gemma":[0.04281611,0.000495187,0.001173067,0.002688868,0.002412651,0.01830122,0.005244953,0.005236682,0.009548755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002125756,"about_ca_system_score_gemma":0.00355164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009811679,"about_ca_topic_score_gemma":0.00561737,"domain_scores_codex":[0.9956952,0.002473906,0.000193171,0.0004231419,0.0009331086,0.0002815616],"domain_scores_gemma":[0.9885514,0.00512705,0.0005429193,0.002276701,0.002129328,0.00137262],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001180572,0.00004373732,0.002322857,0.0003689361,0.00008286014,0.00008642443,0.0003775746,0.01277141,0.0001248696,0.3944575,0.4678145,0.1214313],"study_design_scores_gemma":[0.00004285859,0.00004105449,0.0006447881,0.0004152565,0.00003119346,0.00006449084,0.0002948416,0.0103481,0.0001917721,0.2336235,0.7542218,0.00008041797],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.009620583,0.02267457,0.1959274,0.5677168,0.02631935,0.0001185864,0.01733044,0.0133456,0.1469467],"genre_scores_gemma":[0.3816357,0.0667114,0.2951217,0.1206656,0.01557991,0.0009431877,0.0461667,0.02059076,0.05258511],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02004709,"threshold_uncertainty_score":0.06706423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03407776535959613,"score_gpt":0.251067276904255,"score_spread":0.2169895115446589,"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."}}