{"id":"W4396832250","doi":"10.1145/3613904.3642459","title":"Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking","year":2024,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"Limiting; Echo (communications protocol); Computer science; Polarization (electrochemistry); Keyword search; Psychology; Internet privacy; Computer security; Information retrieval; Engineering","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":[0.007104793,0.0004026424,0.0005066069,0.0004016219,0.0009414644,0.003336916,0.0005190151,0.001373247,0.01003976],"category_scores_gemma":[0.07396958,0.0004020034,0.0004252414,0.0002882644,0.001043069,0.003273743,0.002805821,0.001684824,0.001241285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000660394,"about_ca_system_score_gemma":0.0006036032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00118004,"about_ca_topic_score_gemma":0.000966798,"domain_scores_codex":[0.9944069,0.004207918,0.0002305503,0.0005091637,0.0003860274,0.0002594705],"domain_scores_gemma":[0.8914721,0.09457919,0.004937519,0.00516683,0.001368281,0.00247617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.04028819,0.009098921,0.3047915,0.004059756,0.0009941657,0.00138788,0.1084714,0.01399669,0.1648048,0.05971395,0.01194185,0.2804508],"study_design_scores_gemma":[0.005366723,0.02213275,0.5597951,0.001514201,0.002814399,0.001809338,0.05951402,0.1274469,0.05938007,0.09443276,0.06496757,0.0008262266],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842687,0.0002805105,0.002098294,0.0007340283,0.00004685079,0.00009252362,0.0001225556,0.0001231712,0.01223341],"genre_scores_gemma":[0.9969636,0.00007484498,0.001373541,0.0003277945,0.00002962706,0.0001010395,0.0000925823,0.0000475302,0.0009894927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01003976,"threshold_uncertainty_score":0.03757423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02109711608346044,"score_gpt":0.2711260804428738,"score_spread":0.2500289643594134,"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."}}