{"id":"W2952884488","doi":"10.48550/arxiv.1501.00994","title":"Online Reputation and Polling Systems: Data Incest, Social Learning and Revealed Preferences","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Polling; Overconfidence effect; Polling system; Computer science; Reputation; Parsing; Social learning; Misinformation; Graph; Machine learning; Social psychology; Artificial intelligence; Psychology; Computer security; Theoretical computer science; Knowledge management","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":[0.002542649,0.0001883738,0.0003649365,0.0002215025,0.0003718019,0.0003352138,0.001001469,0.0002155146,0.000017272],"category_scores_gemma":[0.0008693999,0.0001786499,0.00003291311,0.0004536414,0.0002651361,0.000422285,0.002053038,0.0004820071,0.00002012816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004369523,"about_ca_system_score_gemma":0.0001545157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001531444,"about_ca_topic_score_gemma":0.000100212,"domain_scores_codex":[0.9975283,0.0005917652,0.0003485871,0.001154494,0.0002083668,0.0001685461],"domain_scores_gemma":[0.997636,0.0006745221,0.0005711262,0.0006507222,0.0003324894,0.0001352022],"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":[0.000744845,0.0007077473,0.1778903,0.0006745211,0.0005960366,0.0002057339,0.01415746,0.2792343,0.0002591556,0.4654296,0.004565923,0.05553435],"study_design_scores_gemma":[0.0007369228,0.00007434963,0.01157898,0.00020498,0.0002618003,0.00001389612,0.02147583,0.4545064,0.000003789268,0.5033421,0.007149206,0.0006517525],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826729,0.0003790022,0.01465674,0.0001265402,0.0001261754,0.0002630431,0.0002105518,0.00007372107,0.001491298],"genre_scores_gemma":[0.9966087,0.0002599501,0.000214527,0.00001220646,0.0001381755,7.810333e-7,0.000181565,0.000009459,0.002574629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1752721,"threshold_uncertainty_score":0.728513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5043780155849001,"score_gpt":0.3403517486627036,"score_spread":0.1640262669221965,"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."}}