{"id":"W2086305148","doi":"10.1108/09653561211256198","title":"Assessing emergency management training and exercises","year":2012,"lang":"en","type":"article","venue":"Disaster Prevention and Management An International Journal","topic":"Disaster Management and Resilience","field":"Social Sciences","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Training (meteorology); Emergency management; Government (linguistics); Originality; Local government; Engineering; Knowledge management; Qualitative research; Process management; Political science; Computer science; Public administration; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000948309,0.0001214629,0.00009782339,0.0002424472,0.0004883334,0.000820565,0.0002909527,0.00003093581,0.0005173254],"category_scores_gemma":[0.000007524873,0.0001152042,0.00005584944,0.00009474511,0.0001009087,0.003673739,0.0001949996,0.00008228046,0.00001123028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003987093,"about_ca_system_score_gemma":0.000006269997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007866089,"about_ca_topic_score_gemma":0.00002632329,"domain_scores_codex":[0.9985185,0.0001469032,0.000270438,0.0001895534,0.000550498,0.0003241405],"domain_scores_gemma":[0.9995001,0.000008170509,0.0001413182,0.00008328609,0.00004943781,0.0002176706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0000199022,0.0002506082,0.02401261,0.00004180827,0.0002326736,0.00002080659,0.02485496,0.000002798029,0.000007820669,0.2048473,0.0009368019,0.7447719],"study_design_scores_gemma":[0.0014733,0.0000665937,0.3365304,0.0003106801,0.0002951699,0.00003379133,0.3074893,0.0001136756,0.00000301106,0.01808302,0.3350433,0.0005577196],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6146566,0.0004199504,0.01456703,0.0008844507,0.003572923,0.0004127168,0.000001120516,0.00006899169,0.3654163],"genre_scores_gemma":[0.9725131,0.006084246,0.00242681,0.000144614,0.0005874082,0.00001738215,0.000009486961,0.00001093077,0.01820605],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7442142,"threshold_uncertainty_score":0.7912727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0632668508873103,"score_gpt":0.397907553510573,"score_spread":0.3346407026232627,"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."}}