{"id":"W2935993889","doi":"10.1016/j.ijdrr.2019.101148","title":"How useful are earthquake early warnings? The case of the 2017 earthquakes in Mexico city","year":2019,"lang":"en","type":"article","venue":"International Journal of Disaster Risk Reduction","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Instituto Politécnico Nacional; Consejo Nacional de Ciencia y Tecnología; Swine Innovation Porc","keywords":"Seismology; Forensic engineering; Urban seismic risk; Earthquake scenario; Geography; Geology; Engineering; Seismic hazard","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006460047,0.0001236165,0.0002013461,0.0001625166,0.000113228,0.0001459712,0.0009356237,0.00006423475,0.00001172789],"category_scores_gemma":[0.0001940562,0.0000715367,0.0001938893,0.0002036075,0.0001681506,0.0008717679,0.0001920106,0.0004752766,0.00001039021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003566422,"about_ca_system_score_gemma":0.0000467308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001218348,"about_ca_topic_score_gemma":0.0001133749,"domain_scores_codex":[0.9985879,0.0002918031,0.0003882998,0.000179719,0.000397118,0.0001551649],"domain_scores_gemma":[0.9981024,0.0001313875,0.0009920466,0.0003282342,0.0004130026,0.00003289917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001889272,0.0001973655,0.9183582,0.000009766565,0.0004201662,0.0002893372,0.0253378,0.001968747,0.000348539,0.001534244,0.001123573,0.05022335],"study_design_scores_gemma":[0.0007105323,0.0001415953,0.9843494,0.0001110163,0.00002257619,0.004663188,0.003570574,0.0006228397,0.0009546088,0.002935381,0.001811049,0.0001072013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843869,0.0002408964,0.00192123,0.009287248,0.003905362,0.0001157388,0.000005905993,0.000007199295,0.0001295665],"genre_scores_gemma":[0.9989446,0.00006696599,0.0002207691,0.00007480368,0.0002578391,0.000002048157,2.578397e-7,0.00000510095,0.0004275653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06599125,"threshold_uncertainty_score":0.2917182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0152391957375065,"score_gpt":0.2427471966703357,"score_spread":0.2275080009328292,"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."}}