{"id":"W4388535687","doi":"10.3982/te4916","title":"Robust contracting under double moral hazard","year":2023,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Moral hazard; Principal (computer security); Microeconomics; Liability; Limited liability; Risk neutral; Constant (computer programming); Production (economics); Economics; Risk aversion (psychology); Mathematical economics; Business; Computer science; Expected utility hypothesis; Incentive; Finance; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00734293,0.001284074,0.001617674,0.0007874221,0.0006237933,0.002194899,0.002023111,0.002997293,0.004530229],"category_scores_gemma":[0.0210608,0.000759928,0.001383268,0.0006858321,0.003069666,0.00345439,0.0025997,0.002838807,0.000566293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00208475,"about_ca_system_score_gemma":0.001275934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001909871,"about_ca_topic_score_gemma":0.0005141939,"domain_scores_codex":[0.9960724,0.002103801,0.0001545221,0.0005696624,0.0004776949,0.0006219369],"domain_scores_gemma":[0.9806035,0.01180277,0.004150768,0.001303226,0.0008096793,0.001330126],"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":[0.000276758,0.000171783,0.001086406,0.0001675821,0.0001214783,0.000671113,0.0002922435,0.3850134,0.001755869,0.6005891,0.001250174,0.008604128],"study_design_scores_gemma":[0.0001156511,0.0001310001,0.0003509163,0.00002770355,0.00002610873,0.0001153118,0.0000637052,0.7612135,0.0003511317,0.2366004,0.0009750716,0.00002950786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2540189,0.001523874,0.7048571,0.002475935,0.0001581117,0.0001559556,0.0003189591,0.0002357064,0.03625552],"genre_scores_gemma":[0.9603288,0.0006264996,0.02643241,0.0001662733,0.0001472179,0.0001378177,0.0001003062,0.0000587289,0.01200199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00734293,"threshold_uncertainty_score":0.03883362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1972143352121489,"score_gpt":0.3668936448631541,"score_spread":0.1696793096510052,"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."}}