{"id":"W2086533598","doi":"10.1145/1982185.1982225","title":"Towards discovering criminal communities from textual data","year":2011,"lang":"en","type":"article","venue":"","topic":"Digital and Cyber Forensics","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Law enforcement; Suspect; Computer science; Digital forensics; Closeness; Criminal investigation; Data science; Social network analysis; Unit (ring theory); World Wide Web; Information retrieval; Social media; Computer security; Criminology; Political science; Law; Sociology; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005870222,0.00008238752,0.0000810111,0.00001927261,0.00005896984,0.0002174217,0.002396826,0.00001839163,0.0001041793],"category_scores_gemma":[0.00000487238,0.00006332034,0.00001997901,0.00006264474,0.00007876655,0.001663113,0.002605986,0.00006678823,0.0001033233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005931164,"about_ca_system_score_gemma":0.00003161762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008780466,"about_ca_topic_score_gemma":0.0009193937,"domain_scores_codex":[0.9994326,0.00001245674,0.0001025343,0.0001568624,0.000145355,0.0001501392],"domain_scores_gemma":[0.9986541,0.00002223789,0.0000207906,0.001232035,0.00001870767,0.00005215912],"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":[0.000005522636,0.00009817792,0.000789775,0.000004433732,0.00002615655,0.00001782574,0.01073064,8.103214e-7,0.00001422889,0.654178,0.003457261,0.3306772],"study_design_scores_gemma":[0.001901427,0.0009229738,0.149672,0.0002360297,0.0001455135,0.0001358077,0.06897523,0.1424082,0.0223478,0.5127163,0.09711965,0.003419038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1127541,0.00003550649,0.3806755,0.00008071451,0.0002603217,0.00003221361,0.00008265981,0.0001913478,0.5058876],"genre_scores_gemma":[0.9469939,0.000004346417,0.05212322,0.0003285783,0.00003533136,0.000001015359,0.00006315616,0.000003953765,0.0004465126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8342398,"threshold_uncertainty_score":0.9978201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1479071816936467,"score_gpt":0.2591536665290683,"score_spread":0.1112464848354217,"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."}}