{"id":"W3122096277","doi":"10.1287/mnsc.2020.3683","title":"Joint vs. Separate Crowdsourcing Contests","year":2020,"lang":"en","type":"article","venue":"Management Science","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"CONTEST; Crowdsourcing; Incentive; Randomness; Joint (building); Computer science; Microeconomics; Operations research; Economics; Mathematics; Statistics; Engineering; World Wide Web","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":[0.0006647201,0.00009378401,0.0001259262,0.00006639157,0.001071786,0.0002661275,0.0005432019,0.00001489012,0.0001189713],"category_scores_gemma":[0.00005653372,0.00009761403,0.00003915886,0.0005772861,0.0009927164,0.0004771938,0.0004492429,0.00005767173,0.0004753427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001982698,"about_ca_system_score_gemma":0.00003534724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003605564,"about_ca_topic_score_gemma":0.00007763019,"domain_scores_codex":[0.9986031,0.0000281743,0.0001668669,0.0004045324,0.0003761506,0.0004211909],"domain_scores_gemma":[0.9995413,0.00001130769,0.00006830676,0.0001404914,0.0000328718,0.0002057123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005690828,0.000208183,0.08948275,0.00006774443,0.00005694501,0.0001330743,0.1311259,0.0004998879,0.03005664,0.7105964,0.02248177,0.01523379],"study_design_scores_gemma":[0.00294674,0.0007061484,0.1638124,0.0001796946,0.0001408255,0.000002158959,0.1837612,0.004828596,0.04970613,0.005913001,0.5851154,0.002887701],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4797422,0.00007644063,0.0002253853,0.01229745,0.000361976,0.0004465298,0.000001545695,0.0001854465,0.506663],"genre_scores_gemma":[0.9950681,0.0000452589,0.001102414,0.002367529,0.00006503877,0.00002141114,2.96587e-7,0.000005782396,0.001324141],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7046834,"threshold_uncertainty_score":0.8243422,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07375452277205599,"score_gpt":0.3403048771253577,"score_spread":0.2665503543533017,"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."}}