{"id":"W3137787241","doi":"10.2139/ssrn.3700525","title":"Optimal Auction Design with Deferred Inspection and Reward","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.002425984,0.0001008503,0.0001413867,0.00009643673,0.000512674,0.0001770588,0.0002170628,0.00004750445,0.00005401775],"category_scores_gemma":[0.000286416,0.00007055724,0.00004443671,0.0005674671,0.00009487557,0.0004209518,0.00002401137,0.0008098304,0.00010023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001488362,"about_ca_system_score_gemma":0.0005073345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003496435,"about_ca_topic_score_gemma":0.00001786614,"domain_scores_codex":[0.9981881,0.0001980371,0.0002849165,0.0002813359,0.0004401488,0.0006074174],"domain_scores_gemma":[0.9992435,0.0001330063,0.0002110134,0.000128909,0.0001468854,0.0001367147],"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":[0.003355408,0.000192561,0.003407049,0.000005001397,0.0003538383,0.00001443333,0.004520898,0.0647387,0.004471942,0.7075928,0.004937973,0.2064094],"study_design_scores_gemma":[0.001490279,0.002089958,0.001543089,0.000009705594,0.00007522293,0.003877423,0.01858727,0.008916281,0.001327652,0.9476947,0.01401425,0.0003741538],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.169284,0.0002454595,0.8255912,0.004391561,0.00005054061,0.0001055519,6.815073e-7,0.00006021586,0.0002707738],"genre_scores_gemma":[0.9968486,0.0002943022,0.001875171,0.0001584303,0.0002840342,0.000007033996,5.995759e-7,0.00001049851,0.0005212864],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8275647,"threshold_uncertainty_score":0.3943126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07125996221903144,"score_gpt":0.3206698294570235,"score_spread":0.2494098672379921,"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."}}