{"id":"W7008901855","doi":"","title":"Data Analytics, The Next Frontier: Taking a Byte Out of Corruption","year":2017,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Language change; Enforcement; Law enforcement; Analytics; Civil society","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":[0.02430792,0.0008604144,0.001036136,0.004904533,0.006930842,0.02584378,0.001617084,0.005707566,0.005305781],"category_scores_gemma":[0.05278932,0.0006500633,0.0008081421,0.006931,0.01398411,0.03659386,0.008635613,0.01824274,0.001905635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005198136,"about_ca_system_score_gemma":0.01100857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004780841,"about_ca_topic_score_gemma":0.007159477,"domain_scores_codex":[0.9806535,0.009645009,0.0006859477,0.001163148,0.006130627,0.00172171],"domain_scores_gemma":[0.936286,0.04378928,0.002005102,0.004121589,0.008222172,0.005575818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005447216,0.00004625471,0.001890355,0.0002489279,0.00003535618,0.0001137975,0.005022319,0.0003568386,0.0003012348,0.2930788,0.6071643,0.09168734],"study_design_scores_gemma":[0.00001294915,0.00002218895,0.000752526,0.0007435259,0.0000115239,0.00006018403,0.006792803,0.00123078,0.0004455984,0.1893972,0.8004845,0.00004618564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002760496,0.01916102,0.01431054,0.934993,0.009952188,0.00003706207,0.0003782379,0.0003717522,0.01803567],"genre_scores_gemma":[0.2857593,0.1067402,0.04993275,0.4415783,0.06586637,0.0003805534,0.00168999,0.001911922,0.04614064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02584378,"threshold_uncertainty_score":0.1285541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06674270225713465,"score_gpt":0.2752906052173562,"score_spread":0.2085479029602216,"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."}}