{"id":"W2049095485","doi":"10.1109/cogsima.2013.6523839","title":"An ontology-based Social Network Analysis prototype","year":2013,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Situation awareness; Covert; Data science; Ontology; Social network analysis; Context (archaeology); Social network (sociolinguistics); Intelligence analysis; Set (abstract data type); Knowledge management; Computer security; World Wide Web; Social media","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":[0.0001789869,0.00008245373,0.0001410552,0.00009707759,0.0002539065,0.0001729222,0.0004411844,0.00009005681,0.000880514],"category_scores_gemma":[0.000003694974,0.00006999139,0.00009766906,0.001192267,0.00003001677,0.0004729441,0.00004301659,0.0001037545,0.0001996419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000172598,"about_ca_system_score_gemma":0.00003185059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002748297,"about_ca_topic_score_gemma":0.0004416513,"domain_scores_codex":[0.9990809,0.0001123215,0.0001455976,0.0002713226,0.0001426317,0.0002472159],"domain_scores_gemma":[0.9994439,0.00002364884,0.00005364665,0.0003185107,0.00008780356,0.00007252634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008511888,0.0006865187,0.02112516,0.00002112611,0.0006154862,0.00001079679,0.001247265,0.03891885,0.0008342552,0.3816089,0.05546214,0.4993843],"study_design_scores_gemma":[0.000130163,0.0002133176,0.02675289,0.000001053756,0.00002673491,6.410132e-7,0.000005077982,0.9562752,0.0001869477,0.01173497,0.004531009,0.0001419357],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05056822,0.00001321215,0.9423221,0.001903536,0.0002303091,0.0003818377,1.649142e-7,0.0003756963,0.004204863],"genre_scores_gemma":[0.9649308,6.417439e-7,0.03295389,0.001655895,0.0002686392,0.00008990063,0.000003224578,0.000003230727,0.00009372868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9173564,"threshold_uncertainty_score":0.9641011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01149061622335149,"score_gpt":0.2467183196355542,"score_spread":0.2352277034122028,"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."}}