{"id":"W4390979331","doi":"10.36371/port.2023.special.5","title":"Risk and Emergency Management System to Mitigate Disasters","year":2024,"lang":"en","type":"article","venue":"Journal Port Science Research","topic":"Knowledge Management and Technology","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Emergency management; Government (linguistics); Geographic information system; Risk management; Environmental planning; Business; Landslide; Risk analysis (engineering); Disaster response; Environmental resource management; Geography; Computer security; Computer science; Engineering; Political science; Remote sensing; Environmental science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001660467,0.0007952781,0.000558907,0.001722375,0.0009952839,0.003018733,0.001437122,0.0009405642,0.01594678],"category_scores_gemma":[0.00333087,0.0002381179,0.000536809,0.0009416537,0.0002472105,0.00283299,0.001920026,0.0007886491,0.00732352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000816384,"about_ca_system_score_gemma":0.001689909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002467958,"about_ca_topic_score_gemma":0.001315208,"domain_scores_codex":[0.9991226,0.0001895865,0.0001525402,0.0001648014,0.0002777519,0.00009270453],"domain_scores_gemma":[0.9986624,0.000265127,0.0001799371,0.0001959857,0.0005800745,0.0001165422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005581902,0.0006257682,0.01429214,0.0008734729,0.0002210819,0.001219353,0.001475811,0.03913321,0.01246512,0.05378644,0.2539153,0.6214341],"study_design_scores_gemma":[0.0002511674,0.0004392283,0.01279259,0.0004888254,0.0003107931,0.00140468,0.001500916,0.3115551,0.01852716,0.04608652,0.6063922,0.0002508665],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0574359,0.003417419,0.6660509,0.0107005,0.001596642,0.002889337,0.01055453,0.07778766,0.1695671],"genre_scores_gemma":[0.6411335,0.003208111,0.2513925,0.002165447,0.0007820032,0.001872265,0.01375938,0.0008567575,0.08482997],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01594678,"threshold_uncertainty_score":0.05334729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1449991079264008,"score_gpt":0.4875143046561793,"score_spread":0.3425151967297785,"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."}}