{"id":"W6886060821","doi":"10.14288/1.0441528","title":"Visualizing the impact of natural disaster disruption events with 511 data : a case study in the province of British Columbia, Canada","year":2024,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Infrastructure Resilience and Vulnerability Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Natural disaster; Pairwise comparison; Kernel density estimation; Event (particle physics); Natural hazard; Impact assessment; Estimation; Natural (archaeology)","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":[0.0004089559,0.0004122568,0.0002765679,0.00352127,0.002317468,0.001969709,0.0007732976,0.0004099167,0.002710119],"category_scores_gemma":[0.002239405,0.0002203476,0.0003063713,0.009901602,0.0007150597,0.000437739,0.000867883,0.0004649096,0.0003201832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01608209,"about_ca_system_score_gemma":0.01331253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9823089,"about_ca_topic_score_gemma":0.9931166,"domain_scores_codex":[0.9994468,0.00006431151,0.00002336154,0.00007142123,0.0002582317,0.0001359731],"domain_scores_gemma":[0.9986671,0.0003199061,0.00007659039,0.00007073051,0.0007345314,0.0001311579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000606977,0.0004062854,0.4890054,0.001186505,0.0002844523,0.007549295,0.01802991,0.1085402,0.008911172,0.008252041,0.07434019,0.2828875],"study_design_scores_gemma":[0.00006186563,0.00008184359,0.7000929,0.0004260558,0.0001385775,0.0006622188,0.06932674,0.1285123,0.004518764,0.002592776,0.09340305,0.0001829052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.94153,0.0005941844,0.004139618,0.001205651,0.00003242583,0.0002116956,0.03117348,0.0005191998,0.02059364],"genre_scores_gemma":[0.9664935,0.0006306852,0.01296428,0.00006956374,0.000006725102,0.00007020078,0.01391005,0.00007693456,0.005778024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01769108,"threshold_uncertainty_score":0.1166843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007798074730360035,"score_gpt":0.2195374164639823,"score_spread":0.2117393417336223,"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."}}