{"id":"W3108087226","doi":"10.20517/jsss.2020.08","title":"Resilience properties and metrics: how far have we gone?","year":2020,"lang":"en","type":"article","venue":"Journal of Surveillance Security and Safety","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Conseil Régional de Bretagne","keywords":"Resilience (materials science); Variety (cybernetics); Computer security; Field (mathematics); Computer science; Data science; Political science; Internet privacy; Engineering ethics; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008965096,0.0001436885,0.0003389527,0.0001018612,0.0002220086,0.0002387566,0.0003714177,0.00008868516,0.000005715172],"category_scores_gemma":[0.0002995283,0.0001111807,0.00006962586,0.0004247309,0.0001280719,0.0009319057,0.0002261062,0.0004203454,0.000001468992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002234498,"about_ca_system_score_gemma":0.0000502632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000974381,"about_ca_topic_score_gemma":0.00002840474,"domain_scores_codex":[0.9986098,0.0002016412,0.0003581889,0.0002549353,0.0003684353,0.0002069991],"domain_scores_gemma":[0.9989636,0.0001340958,0.0003036157,0.000148644,0.000218418,0.0002316567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003174459,0.0004283627,0.06329077,0.001243957,0.0003894445,0.0004802149,0.07796521,0.000835275,0.008680656,0.0246095,0.01125045,0.8076517],"study_design_scores_gemma":[0.005387524,0.004862134,0.06163333,0.0005594699,0.00004537366,0.001952432,0.004211681,0.3717729,0.007050882,0.01617986,0.524579,0.001765437],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7077559,0.05695869,0.1255458,0.1072861,0.001160172,0.0003911489,0.00001620698,0.0001296389,0.0007563987],"genre_scores_gemma":[0.9773984,0.02042548,0.001292845,0.0006260256,0.0002361467,5.684902e-7,1.700012e-7,0.000004968262,0.00001540486],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8058863,"threshold_uncertainty_score":0.4533816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02524760935146536,"score_gpt":0.214164242078995,"score_spread":0.1889166327275296,"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."}}