{"id":"W3146761840","doi":"10.25245/rdspp.v9i1.800","title":"ARTIFICIAL INTELLIGENCE, LAW AND THE 2030 AGENDA FOR SUSTAINABLE DEVELOPMENT","year":2021,"lang":"en","type":"article","venue":"Revista Direitos Sociais e Políticas Públicas (UNIFAFIBE)","topic":"Smart Cities and Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Guideline; Sustainable development; China; Political science; Order (exchange); Management science; Engineering ethics; Law; Engineering; Business","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":[0.01196197,0.0004347975,0.0006411399,0.003850113,0.004838558,0.01463325,0.00119856,0.006478542,0.003386657],"category_scores_gemma":[0.008731506,0.0002462023,0.0005238161,0.005318319,0.02928753,0.01296625,0.004221343,0.005965942,0.000736326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01111084,"about_ca_system_score_gemma":0.01681458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007585177,"about_ca_topic_score_gemma":0.008224476,"domain_scores_codex":[0.9922037,0.00475874,0.0003817816,0.0004951817,0.001604464,0.0005560529],"domain_scores_gemma":[0.9910898,0.005931865,0.0008643073,0.0005367041,0.001155616,0.0004217026],"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":[0.00000207537,0.000008447863,0.0001581094,0.00004702467,0.000002182405,0.00003135435,0.0007215677,0.0002198832,0.0000259364,0.9917032,0.002449619,0.004630705],"study_design_scores_gemma":[0.000002902967,0.00001152358,0.0003954135,0.0005445112,0.000003428774,0.00004890164,0.003723751,0.0004318616,0.000081291,0.8847786,0.1099647,0.00001307863],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01300951,0.03706721,0.02015586,0.2795848,0.001388595,0.0001117729,0.0001449919,0.00008786984,0.6484495],"genre_scores_gemma":[0.8140607,0.05563506,0.03924894,0.04734578,0.001508977,0.0006142136,0.0003109253,0.00007794713,0.04119756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01463325,"threshold_uncertainty_score":0.08061516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684925680113986,"score_gpt":0.2660209191370974,"score_spread":0.2391716623359575,"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."}}