{"id":"W2608245704","doi":"10.1257/mic.20140272","title":"Disclosure and Legal Advice","year":2017,"lang":"en","type":"article","venue":"American Economic Journal Microeconomics","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Adjudication; Advice (programming); Perspective (graphical); Legal advice; Outcome (game theory); Business; Law and economics; Private information retrieval; Law; Political science; Public relations; Economics; Computer science; Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001201171,0.0003900283,0.001377682,0.0002863734,0.001368909,0.002077895,0.001207683,0.0001432069,0.000376877],"category_scores_gemma":[0.00009854641,0.0005662471,0.0003506019,0.00002640453,0.001399543,0.001851203,0.0003282698,0.0005077808,0.001988414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000696785,"about_ca_system_score_gemma":0.0001350516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005073095,"about_ca_topic_score_gemma":0.001087435,"domain_scores_codex":[0.9965261,0.00003197365,0.001747007,0.0008615711,0.00002113493,0.0008122018],"domain_scores_gemma":[0.994505,0.0000784684,0.00378465,0.001093216,0.00002911927,0.0005094919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001253945,0.00009165827,0.5276967,0.00003118172,0.0006613279,0.00005136998,0.0004933602,0.0001595095,0.00003985177,0.4398282,0.009567482,0.02125393],"study_design_scores_gemma":[0.003574274,0.0004556011,0.1299991,0.0000601524,0.00006310101,0.002638107,0.001427515,0.002639663,0.00009138411,0.1113139,0.7454869,0.002250251],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8920901,0.00123838,0.0002573074,0.003956324,0.00302384,0.0002497295,0.0003355429,0.0000606564,0.09878811],"genre_scores_gemma":[0.991276,0.003109871,0.0009935781,0.0009994054,0.001955657,0.0000151025,0.000008498524,0.00010806,0.001533878],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7359195,"threshold_uncertainty_score":0.9999312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01330582806028009,"score_gpt":0.2246916355209292,"score_spread":0.2113858074606491,"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."}}