{"id":"W2983020321","doi":"","title":"Created Unequal: Bundling with Crowdsourced Products","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Bundle; Business; Incentive; Service provider; Product (mathematics); Marketing; Complementary good; Advertising; Service (business); Industrial organization; Microeconomics; Economics","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":[0.004493284,0.0004654786,0.0005197431,0.00112351,0.001811964,0.003317592,0.001276722,0.0009407909,0.01356006],"category_scores_gemma":[0.0141703,0.0004240062,0.0006559795,0.001273605,0.001530785,0.005032784,0.004528004,0.001192169,0.001610245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157973,"about_ca_system_score_gemma":0.001443735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002313287,"about_ca_topic_score_gemma":0.002853067,"domain_scores_codex":[0.996732,0.001352625,0.0001128941,0.0005441678,0.0009275246,0.0003308032],"domain_scores_gemma":[0.9926587,0.002498783,0.0005842479,0.002802364,0.000669431,0.0007866047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001184896,0.001246931,0.01540724,0.0003813774,0.0001985084,0.0009804241,0.005325492,0.04388629,0.016313,0.4235749,0.01000782,0.4814931],"study_design_scores_gemma":[0.0003432893,0.001049106,0.01146763,0.0002464308,0.0002392178,0.0008237628,0.003412224,0.3611964,0.01009516,0.5103622,0.1005979,0.0001667216],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4539103,0.0004254978,0.4313053,0.001574446,0.0001756716,0.0007874751,0.0002616002,0.00102175,0.110538],"genre_scores_gemma":[0.8906437,0.000119563,0.09650356,0.0001894384,0.00003464584,0.0002013914,0.0001722029,0.0001220053,0.01201356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01356006,"threshold_uncertainty_score":0.04536289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006329059687839602,"score_gpt":0.1676113485797094,"score_spread":0.1612822888918698,"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."}}