{"id":"W2950039849","doi":"10.1108/jcrpp-03-2019-0017","title":"Developing a risk/need assessment tool for women offenders: a gender-informed approach","year":2019,"lang":"en","type":"article","venue":"Journal of Criminological Research Policy and Practice","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada","funders":"","keywords":"Criminal justice; Psychology; Risk assessment; Risk management tools; Originality; Intervention (counseling); Clinical psychology; Applied psychology; Social psychology; Psychiatry; Criminology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02271971,0.0008073685,0.000763901,0.005908629,0.001595472,0.002146248,0.00132575,0.0005060585,0.003516205],"category_scores_gemma":[0.04410126,0.0004056627,0.001025836,0.001846879,0.0009162937,0.002267914,0.002717015,0.001080365,0.0005310086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002443178,"about_ca_system_score_gemma":0.007285252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009960488,"about_ca_topic_score_gemma":0.0316695,"domain_scores_codex":[0.9914824,0.004610356,0.001051359,0.0003888597,0.00204682,0.0004203719],"domain_scores_gemma":[0.9797379,0.00850838,0.003476877,0.001134137,0.006291384,0.000851359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004780375,0.0008417609,0.444254,0.001154333,0.0001377525,0.0006359516,0.02220821,0.0008598781,0.002794076,0.004352046,0.006544416,0.5157395],"study_design_scores_gemma":[0.0002198923,0.002520188,0.7716027,0.005318047,0.0004235485,0.002641144,0.09408521,0.02029359,0.009548214,0.02910302,0.0637696,0.000474914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8359085,0.001939737,0.1084172,0.008569628,0.0004829193,0.01068385,0.002633809,0.0006686256,0.03069564],"genre_scores_gemma":[0.8145701,0.001010984,0.1753618,0.0009447631,0.0000906041,0.004658676,0.0006525854,0.00004881031,0.00266176],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02271971,"threshold_uncertainty_score":0.1201547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4701511581041395,"score_gpt":0.5616593369684509,"score_spread":0.09150817886431145,"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."}}