{"id":"W4393026028","doi":"10.31224/3616","title":"Evaluation of economic disruptions from the 2016 Kumamoto Earthquake using a refined adaptive regional input-output model","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Regional resilience and development","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Science Foundation","keywords":"Computer science; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00177725,0.0002936003,0.0005273015,0.0002565655,0.0001106901,0.0001124077,0.0004514953,0.0002620976,0.0003114324],"category_scores_gemma":[0.0000948626,0.0002471379,0.0003311492,0.0001081214,0.0001413039,0.0001199184,0.0006488301,0.0003908312,0.0005060043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008064914,"about_ca_system_score_gemma":0.001554893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002329463,"about_ca_topic_score_gemma":0.0004372105,"domain_scores_codex":[0.997599,0.00005410066,0.001037001,0.0008298159,0.0002352718,0.0002448114],"domain_scores_gemma":[0.9983326,0.0001500938,0.000612383,0.0006716288,0.0001591289,0.00007421741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000550154,0.00008290087,0.0005910037,0.00003100892,0.0006162435,0.000001190426,0.001319292,0.6332225,0.00001070283,0.3433645,0.01400443,0.006701186],"study_design_scores_gemma":[0.0001691423,0.00001001096,0.003360181,0.0001218813,0.0000593612,8.489396e-7,0.00008121735,0.5544912,0.000006465269,0.4402248,0.001279983,0.0001948862],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8920402,0.01101148,0.03699901,0.004983891,0.001466744,0.001568582,0.001967014,0.00006970543,0.04989341],"genre_scores_gemma":[0.9903095,0.000649254,0.005839875,0.0002797264,0.0002288736,0.000152986,0.0002154482,0.00003724273,0.002287117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09826931,"threshold_uncertainty_score":0.9999981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2327112249310177,"score_gpt":0.3250983356247727,"score_spread":0.09238711069375502,"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."}}