{"id":"W3160282874","doi":"10.2139/ssrn.3809655","title":"Information Aggregation in Large Collective Purchases","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business","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":[0.003389207,0.0003664547,0.001943904,0.001183812,0.001452891,0.003237663,0.001100868,0.002465675,0.007512287],"category_scores_gemma":[0.02451252,0.0007809697,0.0009267309,0.001423916,0.002021139,0.005026462,0.00205731,0.00173606,0.0004396905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001378349,"about_ca_system_score_gemma":0.0007146468,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973347,"about_ca_topic_score_gemma":0.002559154,"domain_scores_codex":[0.9982816,0.0008046505,0.00008902528,0.0002987022,0.000241008,0.0002850138],"domain_scores_gemma":[0.9603064,0.03356306,0.002424136,0.001577984,0.0009663337,0.001162076],"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":[0.0009603822,0.0004748944,0.01205851,0.0005057549,0.0003059925,0.001907472,0.002086419,0.2182874,0.003084733,0.7122884,0.00855398,0.03948598],"study_design_scores_gemma":[0.00008171989,0.0001560084,0.005236531,0.0000461129,0.000069945,0.0002179444,0.0008090023,0.3899124,0.0004742328,0.6017689,0.001175381,0.00005188095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8619764,0.0007529535,0.1068026,0.00358945,0.0001394836,0.0001208867,0.0002384314,0.00021836,0.02616146],"genre_scores_gemma":[0.9924843,0.0001354568,0.003296775,0.00007047195,0.00005436222,0.00003688962,0.00003936745,0.00001693795,0.003865587],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007512287,"threshold_uncertainty_score":0.02513117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588693407653195,"score_gpt":0.3319801122469042,"score_spread":0.3060931781703722,"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."}}