{"id":"W3157054666","doi":"10.2139/ssrn.3802097","title":"Estimating Complementarity With Large Choice Sets: An Application to Mergers","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital; Université du Québec à Montréal; Université de Montréal; University of Calgary","funders":"","keywords":"Complementarity (molecular biology); Economics; Econometrics; Microeconomics; Mathematical economics; 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":[0.03514041,0.001685184,0.007906536,0.005631857,0.003211364,0.003445076,0.005020454,0.003896921,0.01009416],"category_scores_gemma":[0.1446628,0.003431288,0.005038977,0.00762389,0.004398354,0.004938629,0.007649254,0.005486287,0.0007903915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003788091,"about_ca_system_score_gemma":0.003585099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02958057,"about_ca_topic_score_gemma":0.02927633,"domain_scores_codex":[0.9737688,0.02134784,0.000622693,0.001861775,0.00157634,0.0008225616],"domain_scores_gemma":[0.4906357,0.4939706,0.00478055,0.006966307,0.001951015,0.001695863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002930709,0.002683998,0.06207922,0.0006638382,0.002417055,0.001019556,0.001048085,0.662484,0.0007728903,0.1041427,0.005425047,0.1543329],"study_design_scores_gemma":[0.0001966426,0.0002421159,0.004487063,0.0000346593,0.0001622047,0.00009359207,0.0001331709,0.9248592,0.000267779,0.068765,0.0007027203,0.00005582837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3104903,0.001240365,0.6804214,0.001541884,0.00009874104,0.0006414683,0.001228506,0.0008452098,0.003492078],"genre_scores_gemma":[0.7897666,0.0004319957,0.2033823,0.0003294994,0.0001979798,0.0008210685,0.001087855,0.000125935,0.003856823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03514041,"threshold_uncertainty_score":0.1858425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313580140728728,"score_gpt":0.2732667251626825,"score_spread":0.2601309237553952,"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."}}