{"id":"W7116407513","doi":"10.5281/zenodo.17998130","title":"PRACTICAL AND METHODOLOGICAL ASPECTS OF STAFFING POLICE FORCES IN ADVANCED FOREIGN COUNTRIES","year":2025,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Policing Practices and Perceptions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Staffing; Law enforcement; Enforcement; Human resource management; Human resources","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02744938,0.0002965174,0.0001994832,0.005053317,0.004724097,0.003980897,0.0006887505,0.0008180166,0.001198107],"category_scores_gemma":[0.03273336,0.000197545,0.0001662162,0.005239557,0.008590922,0.002301814,0.0027854,0.0007484251,0.0001203048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007093418,"about_ca_system_score_gemma":0.01139564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008814245,"about_ca_topic_score_gemma":0.009255417,"domain_scores_codex":[0.9740989,0.02087384,0.0009996826,0.0006954725,0.00199374,0.001338467],"domain_scores_gemma":[0.9813029,0.0109776,0.00312534,0.0009160422,0.002755692,0.0009224198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002448019,0.000255985,0.122397,0.001344319,0.00005329942,0.001082072,0.4647396,0.002841896,0.001688373,0.2125352,0.001730272,0.1910871],"study_design_scores_gemma":[0.0000260885,0.0004401371,0.1283442,0.001705314,0.00002824501,0.000754007,0.7932669,0.0008745684,0.001623243,0.0217334,0.05114488,0.00005900277],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930545,0.005913826,0.006665167,0.005880257,0.0001352159,0.0001549871,0.00005640466,0.00001021434,0.05063894],"genre_scores_gemma":[0.994359,0.001519743,0.002959803,0.0001900691,0.00003774372,0.00008437556,0.00002184291,0.00000351221,0.0008239287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02744938,"threshold_uncertainty_score":0.1451679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.134861950266441,"score_gpt":0.4160186563420855,"score_spread":0.2811567060756445,"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."}}