{"id":"W4287150833","doi":"10.18280/ijsse.120304","title":"Cybersecurity Training in Norwegian Critical Infrastructure Companies","year":2022,"lang":"en","type":"article","venue":"International Journal of Safety and Security Engineering","topic":"Information and Cyber Security","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Preparedness; Best practice; Norwegian; Maturity (psychological); Business; Critical infrastructure; Training (meteorology); Implementation; Curriculum; Security awareness; Public relations; Computer security; Knowledge management; Engineering; Psychology; Information security; Computer science; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003555696,0.0002478555,0.000179107,0.001044309,0.002653152,0.00156599,0.0004171106,0.000729787,0.002765094],"category_scores_gemma":[0.005296405,0.0003362242,0.000149701,0.0009544684,0.001436547,0.0009510348,0.001241682,0.0006924242,0.0002683063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007977033,"about_ca_system_score_gemma":0.01138474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07575315,"about_ca_topic_score_gemma":0.101526,"domain_scores_codex":[0.9974145,0.0008167097,0.0001882233,0.0002600188,0.0003994999,0.0009210953],"domain_scores_gemma":[0.9887138,0.004270335,0.001539414,0.0002270638,0.001712307,0.00353708],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005298353,0.001451635,0.408512,0.001624568,0.00003108502,0.004576263,0.4711202,0.002776813,0.008341564,0.006384184,0.01043843,0.08421349],"study_design_scores_gemma":[0.00003666942,0.0008687659,0.4468261,0.0008407674,0.00002235345,0.0004936022,0.4956171,0.0009998404,0.001546009,0.0004407758,0.05223197,0.00007610801],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945902,0.0004209245,0.0001896557,0.0006658342,0.00003535406,0.00004783285,0.00006869307,0.000008764332,0.003972872],"genre_scores_gemma":[0.9978568,0.0003773912,0.0002259987,0.000185848,0.000007032253,0.00002995697,0.00005284859,0.000003709457,0.001260413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07575315,"threshold_uncertainty_score":0.1506245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006472811295897037,"score_gpt":0.2274233664677814,"score_spread":0.2209505551718844,"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."}}