{"id":"W1498724620","doi":"","title":"Information Asymmetry in Mauritius Slave Auctions","year":2007,"lang":"en","type":"preprint","venue":"IRIS","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"HEC Montréal","keywords":"Common value auction; Information asymmetry; Bidding; Adverse selection; Spouse; Economics; Business; Microeconomics; Law; Political science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00422357,0.0002659451,0.0009573309,0.001578236,0.0009863004,0.003164698,0.0006823549,0.0009921257,0.007323781],"category_scores_gemma":[0.02850787,0.0002484486,0.0004475014,0.001940554,0.001972183,0.001947325,0.001356714,0.00109906,0.0003866217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001946818,"about_ca_system_score_gemma":0.0006904069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004939108,"about_ca_topic_score_gemma":0.003412649,"domain_scores_codex":[0.9974476,0.001469107,0.0001296813,0.0001866301,0.0004567142,0.000310188],"domain_scores_gemma":[0.9733665,0.01594824,0.008273515,0.001257951,0.0006532174,0.0005005558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002731365,0.000526568,0.3693664,0.0006163705,0.0005059637,0.00383577,0.007039927,0.07924044,0.007219177,0.4008445,0.01107108,0.1170024],"study_design_scores_gemma":[0.0003943843,0.0004033263,0.3955312,0.0002521572,0.0002058986,0.001303183,0.004752493,0.2601283,0.00195658,0.3252044,0.009709448,0.0001587024],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97837,0.0005539022,0.005893706,0.0007143143,0.0000146927,0.00005879853,0.0001923417,0.0000254447,0.01417681],"genre_scores_gemma":[0.9985191,0.000141464,0.0003246135,0.00002591015,0.00001699015,0.00001506167,0.00004519883,0.000002199554,0.0009093535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007323781,"threshold_uncertainty_score":0.02450043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0982145736035989,"score_gpt":0.4237421466102387,"score_spread":0.3255275730066398,"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."}}