{"id":"W3120308649","doi":"","title":"Artificial Intelligence for Sustainable and Effective Justice Delivery in India","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic Justice; Population; Political science; Law; Transformational leadership; Business; Law and economics; Economics; Sociology; Public relations","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":[],"consensus_categories":[],"category_scores_codex":[0.005681233,0.00013272,0.000173962,0.0002055693,0.001268184,0.0001835315,0.0003131814,0.0001421165,0.00004295319],"category_scores_gemma":[0.001650677,0.000134577,0.00005997294,0.0004870933,0.0007303687,0.0005526671,0.00005111564,0.0008670256,0.0000363367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001417839,"about_ca_system_score_gemma":0.0020967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001485295,"about_ca_topic_score_gemma":0.01737254,"domain_scores_codex":[0.9962056,0.000251026,0.0003496169,0.0002613381,0.0002559262,0.00267647],"domain_scores_gemma":[0.9985839,0.0006091868,0.0001304483,0.00009473742,0.0004595921,0.0001222028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001517866,0.00004191771,0.0003741583,0.000008143411,0.00001719303,0.000005600304,0.006675112,0.000009764333,0.00005927521,0.8825764,0.00002735503,0.1100533],"study_design_scores_gemma":[0.00004203375,0.0005528996,0.0001650484,0.00001831314,0.00003652011,0.00001581372,0.1137019,0.0002235979,0.001328056,0.8795178,0.004226547,0.000171487],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8744373,0.001346876,0.1075974,0.001270152,0.0007747955,0.001591603,0.000002076245,0.00006672978,0.01291307],"genre_scores_gemma":[0.996529,0.0009967685,0.0002098643,0.0001206839,0.001338713,0.00003511235,5.002117e-7,0.00001649569,0.0007528445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1220918,"threshold_uncertainty_score":0.9753972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194265939506989,"score_gpt":0.3377412391529303,"score_spread":0.3183146452022313,"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."}}