{"id":"W2995383459","doi":"10.1287/stsc.2019.0092","title":"A Theory of Digital Firm-Designed Markets: Defying Knowledge Constraints with Crowds and Marketplaces","year":2019,"lang":"en","type":"article","venue":"Strategy Science","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; York University","funders":"","keywords":"Crowds; Crowdsourcing; Argument (complex analysis); Order (exchange); Perspective (graphical); Industrial organization; Business; Knowledge management; Computer science; Microeconomics; Economics; Artificial intelligence","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":[0.004980119,0.0007250637,0.001060452,0.002201977,0.002456102,0.006339816,0.002133469,0.003576764,0.01049703],"category_scores_gemma":[0.01104106,0.0005190552,0.00156847,0.002289218,0.01535204,0.01350589,0.003401896,0.002344921,0.0007365745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003873396,"about_ca_system_score_gemma":0.002774219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002828218,"about_ca_topic_score_gemma":0.001742717,"domain_scores_codex":[0.9965993,0.001608454,0.0001415959,0.0006581021,0.0006512048,0.0003414501],"domain_scores_gemma":[0.9892592,0.006558478,0.001617185,0.001514924,0.0006247732,0.0004255375],"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":[0.000004951148,0.00001039271,0.0001169276,0.00004059196,0.000007999527,0.00002566576,0.0000814456,0.003800687,0.00005924808,0.9929618,0.000247041,0.002643146],"study_design_scores_gemma":[0.00002316742,0.00002127069,0.0001389678,0.00004166144,0.000009371774,0.00003206994,0.0001021534,0.01344157,0.0001095576,0.9808156,0.005254548,0.00001004658],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06992455,0.003561188,0.7387398,0.01302626,0.0002371536,0.0002529769,0.0002345396,0.0001651817,0.1738584],"genre_scores_gemma":[0.8997903,0.001970671,0.08476864,0.001181694,0.0002667668,0.0004461931,0.00007861727,0.00004374475,0.0114534],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01049703,"threshold_uncertainty_score":0.03511608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04993943256680507,"score_gpt":0.3407327765832999,"score_spread":0.2907933440164948,"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."}}