{"id":"W2573523873","doi":"","title":"User Participation and Honesty in Online Rating Systems: What a Social Network Can Do","year":2016,"lang":"en","type":"article","venue":"Edinburgh Research Explorer (University of Edinburgh)","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Recommender system; Baseline (sea); Incentive; Computer science; Honesty; Dilemma; Online participation; Social network (sociolinguistics); Crowdsourcing; Online community; Filter (signal processing); Rating system; Internet privacy; Data science; World Wide Web; Social media; The Internet; Psychology; Microeconomics; Environmental 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002466282,0.0001446198,0.0003538568,0.0002883845,0.001137867,0.0001335048,0.0003513891,0.0001605508,0.0004762772],"category_scores_gemma":[0.000246063,0.0001441103,0.00006551516,0.000622607,0.001332997,0.001498266,0.0004306392,0.0002511323,0.000002706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005927164,"about_ca_system_score_gemma":0.0001930339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006018065,"about_ca_topic_score_gemma":0.005395512,"domain_scores_codex":[0.9975157,0.0003460601,0.0002495218,0.0004291199,0.0006622798,0.0007972763],"domain_scores_gemma":[0.9985899,0.0005423526,0.0001408984,0.0001671537,0.0003375955,0.0002221231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005014551,0.0006762129,0.3428998,0.00003220556,0.0001501595,0.0001451414,0.5118098,0.00007147958,0.005678946,0.009951659,0.09136809,0.03671505],"study_design_scores_gemma":[0.002021667,0.0002493278,0.0178168,0.0006704727,0.0000291805,8.809409e-7,0.9566784,0.0001336438,0.00007526828,0.003738118,0.01811419,0.0004720379],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914936,0.0007193421,0.00003535103,0.005797255,0.0005709852,0.0004868278,0.00001555649,0.0000383026,0.0008428177],"genre_scores_gemma":[0.9951652,0.002551033,0.000137039,0.00001454242,0.0007722752,0.0000105912,0.000005284098,0.00001148751,0.001332534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4448686,"threshold_uncertainty_score":0.9097555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1431412220547272,"score_gpt":0.3830735770927309,"score_spread":0.2399323550380037,"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."}}