{"id":"W7071754527","doi":"","title":"Sursis, récidive et réinsertion sociale : un équilibre précaire","year":2009,"lang":"fr","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Punitive damages; Sentence; Odds; Recidivism; Rehabilitation; Conditional probability","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002776153,0.0003947178,0.0003491259,0.005144336,0.0005279255,0.0002999104,0.001638098,0.0004445148,0.00004176633],"category_scores_gemma":[0.00007193693,0.0004714022,0.0002483961,0.01360298,0.000273131,0.002088708,0.0005834762,0.0005092255,0.0001477957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000449087,"about_ca_system_score_gemma":0.001116135,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01878694,"about_ca_topic_score_gemma":0.004409918,"domain_scores_codex":[0.9975563,0.0002475969,0.0002613264,0.0008965537,0.0003444312,0.0006937346],"domain_scores_gemma":[0.9981513,0.0001032627,0.0002346374,0.001040201,0.0003549191,0.000115666],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002945693,0.0005640693,0.0001862654,0.00002791596,0.00006615086,0.0001599526,0.003711641,0.0000217978,0.00005381953,0.4242771,0.001785281,0.5691165],"study_design_scores_gemma":[0.0007398446,0.0003900271,0.001932632,0.00009409509,0.00009480779,0.00003565528,0.0005123258,0.002327879,0.001712405,0.0005996504,0.9910187,0.0005420499],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08266865,0.0002162076,0.1341257,0.09036978,0.001063034,0.001941614,0.0001334018,0.00275015,0.6867315],"genre_scores_gemma":[0.8047698,0.1718181,0.021211,0.001049074,0.0001561107,0.00000693284,0.00004056225,0.00003289589,0.0009155273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9892334,"threshold_uncertainty_score":0.9997737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424299461871821,"score_gpt":0.2343735970331016,"score_spread":0.2101306024143834,"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."}}