{"id":"W3028011508","doi":"10.18280/ijsse.100217","title":"Object Detection Using Convolutional Neural Networks for Natural Disaster Recovery","year":2020,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Seismology and Earthquake Studies","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Convolutional neural network; Computer science; Object (grammar); Artificial intelligence; Natural disaster; Object detection; Natural (archaeology); Pattern recognition (psychology); Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0001461923,0.00007939586,0.0001279296,0.00005993501,0.00006309408,0.00004894773,0.0002046564,0.00003997455,0.000001719114],"category_scores_gemma":[0.0001176471,0.00007419383,0.00008848469,0.00006119633,0.00002042962,0.0004836021,0.00007712722,0.000199914,1.943051e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003106463,"about_ca_system_score_gemma":0.00001408546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002618207,"about_ca_topic_score_gemma":0.000001507842,"domain_scores_codex":[0.9994036,0.00001476863,0.0002342648,0.0001003336,0.0001382379,0.000108819],"domain_scores_gemma":[0.9995006,0.0001469506,0.0001028712,0.00003071436,0.0001672569,0.00005161389],"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":[0.001093412,0.00003299294,0.0008854539,0.00003959554,0.0006761055,0.00007827111,0.003076577,0.9476593,0.001392195,0.006840748,0.00006185741,0.03816353],"study_design_scores_gemma":[0.0004590113,0.0000894593,0.003251258,0.0000196559,0.000009201277,0.0002911461,0.00003275394,0.9943473,0.0000899352,0.0003912553,0.0009396294,0.00007937938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1407014,0.0008146501,0.8547933,0.001485585,0.002145181,0.0000361118,0.000003631411,0.00001523199,0.000004970015],"genre_scores_gemma":[0.9953662,0.00007492967,0.003434029,0.0004248812,0.0006931326,4.961263e-7,0.000001301006,0.000003732189,0.000001267618],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8546649,"threshold_uncertainty_score":0.3025537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01117914986756481,"score_gpt":0.220745518333583,"score_spread":0.2095663684660182,"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."}}