{"id":"W1993230349","doi":"10.4018/ijss.2014070104","title":"Radicalization and Recruitment","year":2014,"lang":"en","type":"article","venue":"International Journal of Systems and Society","topic":"Information Systems Theories and Implementation","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Radicalization; Terrorism; Apprehension; Process (computing); Through-the-lens metering; Conceptual framework; State (computer science); Computer science; Political science; Criminology; Sociology; Computer security; Lens (geology); Psychology; Law; Engineering; Social science; Cognitive psychology","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":[0.001581535,0.00003543688,0.00008278841,0.00002758389,0.0001593603,0.0001735055,0.00006859085,0.00003623808,0.00001541973],"category_scores_gemma":[0.00006933446,0.00002908182,0.00003726587,0.00003158264,0.0000689013,0.0003464983,0.00001311186,0.00003826054,8.940185e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006033766,"about_ca_system_score_gemma":0.00003359973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001966459,"about_ca_topic_score_gemma":0.00000623005,"domain_scores_codex":[0.9991391,0.00009424472,0.0003054412,0.00003686183,0.0003642431,0.00006011283],"domain_scores_gemma":[0.9992139,0.00006472656,0.0002948999,0.00002172577,0.0003478318,0.00005686921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001365405,0.00001477824,0.005772907,0.00002643239,0.0001332771,6.083627e-7,0.07480166,0.00003195011,0.00009237049,0.884286,0.006905647,0.02792065],"study_design_scores_gemma":[0.0006771685,0.00005808103,0.002476071,0.00008187337,0.00001125003,0.0000337437,0.04854193,0.001203016,0.00001292526,0.001445992,0.9453905,0.00006740355],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7276016,0.001449886,0.2092459,0.00949894,0.01104355,0.0009483421,0.00002302948,0.00004713858,0.04014163],"genre_scores_gemma":[0.9978459,0.000692623,0.0003010179,0.0002039064,0.0007134874,0.000002800643,0.000002098692,0.000002240768,0.000235945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9384849,"threshold_uncertainty_score":0.1673118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0418349686336152,"score_gpt":0.3631229533823722,"score_spread":0.321287984748757,"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."}}