{"id":"W3005689102","doi":"10.21810/jicw.v2i3.1188","title":"Big Data and the Fight Against Extremism","year":2020,"lang":"en","type":"article","venue":"The Journal of Intelligence Conflict and Warfare","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Presentation (obstetrics); Period (music); Panel discussion; Panel data; Political science; Computer security; Media studies; Sociology; Computer science; Advertising; Business; Medicine; Art; Economics","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":[0.00916497,0.0005139102,0.0006077911,0.002353327,0.004653744,0.01165042,0.0008223621,0.005267766,0.008890536],"category_scores_gemma":[0.01355091,0.0003000594,0.0004451732,0.002106405,0.0105685,0.01144535,0.00543002,0.01001772,0.001712822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003915407,"about_ca_system_score_gemma":0.003799897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003199539,"about_ca_topic_score_gemma":0.004618873,"domain_scores_codex":[0.9954464,0.002254018,0.000112889,0.0004359408,0.001104085,0.0006467458],"domain_scores_gemma":[0.9921452,0.004564637,0.0006462852,0.0004992214,0.0009012566,0.001243342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001048375,0.00004052573,0.00107181,0.0001748137,0.00005679446,0.0001062601,0.00118442,0.0005550459,0.0001355527,0.6027893,0.336358,0.05742268],"study_design_scores_gemma":[0.00003587762,0.0000393738,0.001529697,0.0007514708,0.00001472934,0.00007390294,0.002080092,0.0008360894,0.0002509581,0.5063331,0.4880145,0.00004033114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.005252499,0.05922126,0.002315942,0.8329808,0.00899276,0.00002352444,0.000295354,0.000082431,0.09083549],"genre_scores_gemma":[0.5307364,0.1093438,0.006506203,0.2677577,0.01880012,0.0001990048,0.0006132204,0.0002358013,0.0658078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01165042,"threshold_uncertainty_score":0.0484696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08765834849586832,"score_gpt":0.2681296737214456,"score_spread":0.1804713252255773,"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."}}