{"id":"W20059804","doi":"10.1017/s1461145709991167","title":"少年犯罪を防ぐ--予防と更生のプログラム[含 講評]","year":2006,"lang":"en","type":"article","venue":"立正大学社会学論叢","topic":"Polyamine Metabolism and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002723843,0.0002109897,0.0001688916,0.0002225901,0.0001562367,0.0002344211,0.0001221365,0.0002291409,0.006375826],"category_scores_gemma":[0.0003824973,0.0001337341,0.0001046298,0.0001263148,0.0002412227,0.0002408619,0.0001635403,0.0003984308,0.002307935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001783459,"about_ca_system_score_gemma":0.0001764104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004183917,"about_ca_topic_score_gemma":0.0009053171,"domain_scores_codex":[0.9999226,0.000009737695,0.000009215719,0.00002064764,0.00002585335,0.00001190728],"domain_scores_gemma":[0.9998655,0.00002697154,0.00003453758,0.00001379649,0.00003566534,0.00002342953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00060745,0.00008574744,0.01029396,0.0001842914,0.00005233858,0.001070428,0.0001706949,0.0003284287,0.7750701,0.002420574,0.001290105,0.208426],"study_design_scores_gemma":[0.0001101027,0.002201719,0.07987449,0.0000697653,0.00009864095,0.008117459,0.0002665333,0.00365273,0.8631018,0.002709324,0.03974251,0.00005490002],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9328747,0.004948583,0.03791256,0.0005057611,0.0001789907,0.0001500864,0.0005628878,0.0003524239,0.02251403],"genre_scores_gemma":[0.9644382,0.002656002,0.01814085,0.0001340582,0.00004264561,0.00006165907,0.0006749987,0.00005727473,0.01379437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006375826,"threshold_uncertainty_score":0.02132922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002715592027371983,"score_gpt":0.2101027816734821,"score_spread":0.2073871896461102,"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."}}