{"id":"W4415235236","doi":"10.1080/15614263.2025.2574317","title":"Untangling SNA: the use and underuse of social network analysis among crime analysts","year":2025,"lang":"en","type":"article","venue":"Police Practice and Research","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Social network analysis; Network analysis; Social network (sociolinguistics); Crime analysis; Intelligence analysis; Statistical analysis","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00357584,0.000057684,0.0001505239,0.0002917259,0.001601615,0.0003962199,0.0001727938,0.00007232673,0.0001193716],"category_scores_gemma":[0.001196919,0.00004325136,0.00009660368,0.002032077,0.0007492963,0.0004880026,0.000185858,0.0003219931,0.000002261037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003804073,"about_ca_system_score_gemma":0.0000974108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1829188,"about_ca_topic_score_gemma":0.0551519,"domain_scores_codex":[0.9976697,0.001254871,0.0001931231,0.0001760667,0.0003844988,0.0003217395],"domain_scores_gemma":[0.9966177,0.002663418,0.00008823111,0.0001498089,0.0004161355,0.00006464594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001900907,0.0004485669,0.5785809,0.0001359561,0.004390548,0.000008343098,0.1338772,0.0001533705,0.0001581243,0.2244695,0.04871111,0.008876282],"study_design_scores_gemma":[0.0003558317,0.00006311071,0.6854447,0.00007709019,0.001925113,8.359462e-7,0.1564754,0.001250394,0.0000522619,0.001891952,0.1522895,0.0001738376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9560223,0.0007674662,0.000317408,0.01471305,0.00005801122,0.0002196285,0.000007815311,0.0000139965,0.02788039],"genre_scores_gemma":[0.9961899,0.0006691093,0.00006841515,0.0002070611,0.0001717211,0.000008760629,0.000001849847,0.000003692931,0.002679491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2225775,"threshold_uncertainty_score":0.9996982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.211701409533729,"score_gpt":0.5274597458464733,"score_spread":0.3157583363127442,"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."}}