{"id":"W7104438859","doi":"10.71781/23206","title":"Victimisation secondaire : vers la création d’un outil standardisé","year":2022,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Victimisation; Betrayal; Poison control; Victimology","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":[0.12491,0.001185293,0.001826291,0.00752676,0.002150089,0.01099315,0.00385184,0.001667226,0.004309876],"category_scores_gemma":[0.1881493,0.0008202498,0.00215022,0.005255488,0.007320927,0.01003786,0.008132613,0.004431627,0.0009410716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009940867,"about_ca_system_score_gemma":0.01090472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01148654,"about_ca_topic_score_gemma":0.008033804,"domain_scores_codex":[0.8963778,0.05950955,0.01360708,0.006723224,0.02194911,0.001833308],"domain_scores_gemma":[0.7684348,0.1080208,0.02764938,0.03126456,0.06085558,0.003774938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000932718,0.0006362419,0.2636022,0.00323862,0.0009909882,0.0002293017,0.05305767,0.001638774,0.001644522,0.105494,0.01736514,0.5511698],"study_design_scores_gemma":[0.0003032217,0.003153106,0.6312504,0.0132091,0.0009517539,0.0008173853,0.0379597,0.009686397,0.008144964,0.077077,0.2166551,0.0007917634],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5148839,0.01950922,0.3116778,0.04093548,0.006380767,0.007006277,0.005829609,0.001710001,0.09206679],"genre_scores_gemma":[0.8461769,0.004393061,0.1247521,0.003103286,0.0008065206,0.009491383,0.00326979,0.0004176587,0.007589291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.12491,"threshold_uncertainty_score":0.6605953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005832007647715969,"score_gpt":0.2052248364724669,"score_spread":0.1993928288247509,"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."}}