{"id":"W2678752310","doi":"","title":"Money changes everything: Adolescent resources and crime","year":2004,"lang":"en","type":"article","venue":"Criminologie","topic":"Crime, Illicit Activities, and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Business; Criminology; Economics; Computer security; Computer science; Psychology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001100043,0.0002227192,0.0002944039,0.001168199,0.002297829,0.003640545,0.0005143015,0.001291945,0.00905659],"category_scores_gemma":[0.00616363,0.0002627118,0.0002256053,0.001441484,0.003014995,0.002770179,0.001839875,0.001962229,0.0003518662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001875631,"about_ca_system_score_gemma":0.002629909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02728564,"about_ca_topic_score_gemma":0.06471502,"domain_scores_codex":[0.9991539,0.0004363379,0.00002318904,0.00004405011,0.00007559333,0.0002669056],"domain_scores_gemma":[0.9953281,0.001535202,0.001191574,0.0001223524,0.0003338103,0.001488984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001159772,0.0007751076,0.8869859,0.00005433983,0.00005823044,0.0007366724,0.01713664,0.000314294,0.0000748183,0.06413792,0.005650545,0.02395951],"study_design_scores_gemma":[0.00003696711,0.0001487395,0.8332614,0.0003853527,0.0001379632,0.0009113146,0.1143528,0.0009098861,0.0002528516,0.02573012,0.02383636,0.00003624933],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9623513,0.002775057,0.00008718095,0.01519628,0.00006126919,0.00001055561,0.0001225906,0.000002534207,0.01939327],"genre_scores_gemma":[0.9971461,0.001299271,0.0000355797,0.000291708,0.00002350574,0.00000718173,0.00002804453,0.000002480186,0.001166161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02728564,"threshold_uncertainty_score":0.05425364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2501635804165168,"score_gpt":0.3618984802174027,"score_spread":0.111734899800886,"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."}}