{"id":"W3207134617","doi":"10.2139/ssrn.3931256","title":"Legal Priorities Research: A Research Agenda","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Flourishing; Multidisciplinary approach; Humanity; Engineering ethics; Political science; Corporate governance; Theme (computing); Prioritization; Space (punctuation); Sociology; Environmental ethics; Management science; Psychology; Law; Computer science; Business; Social psychology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1234336,0.001648305,0.004927041,0.013722,0.01222035,0.04854493,0.006641852,0.02745538,0.03684381],"category_scores_gemma":[0.1422703,0.00123052,0.001912957,0.01779499,0.02629191,0.04772659,0.01390855,0.01870457,0.003730543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0279545,"about_ca_system_score_gemma":0.1094495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01159416,"about_ca_topic_score_gemma":0.0207027,"domain_scores_codex":[0.9452006,0.04103349,0.003003844,0.002680672,0.004519354,0.003562062],"domain_scores_gemma":[0.6162022,0.2912549,0.01500147,0.007206592,0.04523498,0.02509993],"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":[0.0002140227,0.0004960169,0.0037299,0.005834926,0.0001507832,0.0001595565,0.003195471,0.0005168105,0.0001291676,0.8382178,0.06561385,0.08174165],"study_design_scores_gemma":[0.00016046,0.0001723069,0.001650139,0.02395449,0.0001935932,0.000169641,0.03109211,0.0009627267,0.0002122875,0.7845033,0.1568526,0.00007645795],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.002509418,0.1033103,0.005320616,0.8505014,0.006783355,0.0001958986,0.0002758982,0.0000477493,0.03105528],"genre_scores_gemma":[0.316551,0.3091404,0.03952409,0.282569,0.03199637,0.002885723,0.001269381,0.0002004949,0.01586362],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1234336,"threshold_uncertainty_score":0.6527872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2678368403384869,"score_gpt":0.5220146790567782,"score_spread":0.2541778387182914,"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."}}