{"id":"W4413243547","doi":"10.1145/3759453","title":"A Survey of Conversational Search","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Information Systems","topic":"Topic Modeling","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Semantic search; Context (archaeology); Unison; Search engine; Natural language; Data science; Human–computer interaction; World Wide Web; Information retrieval; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000602113,0.00005798741,0.0001023484,0.0003184773,0.00008474823,0.00008712861,0.0004986364,0.00004907338,0.000007804228],"category_scores_gemma":[0.0000454392,0.00005717297,0.00003134788,0.0005282895,0.00001705195,0.001010016,0.000009812542,0.00008822286,0.00006030104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005463757,"about_ca_system_score_gemma":0.0001704121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007995465,"about_ca_topic_score_gemma":0.00001020493,"domain_scores_codex":[0.9990674,0.00008351748,0.0003937703,0.00008202608,0.0002807658,0.00009257338],"domain_scores_gemma":[0.9988011,0.0002323102,0.00007203894,0.0005285759,0.0003401061,0.00002584434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005299033,0.0001261607,0.004963432,0.0005455191,0.0002046223,4.149145e-7,0.006425365,0.5541232,0.00008210474,0.1969564,0.0007600726,0.2357597],"study_design_scores_gemma":[0.0007223128,0.0000430206,0.02323084,0.00009267439,0.000005657038,0.000003358364,0.0004358368,0.9708231,0.00139945,0.0002231325,0.002883186,0.0001373984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003312797,0.0000138599,0.9933715,0.0002798527,0.0006574129,0.000182043,0.00002653972,0.00006442662,0.002091526],"genre_scores_gemma":[0.995971,0.00000389748,0.003703151,0.000103428,0.000004127588,0.00002145909,0.00001123355,0.000001187083,0.0001804713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9926583,"threshold_uncertainty_score":0.2331446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433947417254156,"score_gpt":0.2822650442032452,"score_spread":0.2388703024778296,"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."}}