{"id":"W4396832608","doi":"10.1145/3613905.3636287","title":"CUI@CHI 2024: Building Trust in CUIs—From Design to Deployment","year":2024,"lang":"en","type":"article","venue":"","topic":"AI in Service Interactions","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Waterloo; University of Toronto","funders":"","keywords":"Breakout; Usability; Multidisciplinary approach; Software deployment; Computer science; Order (exchange); Human–computer interaction; Human interaction; Knowledge management; Sociology; Business; Software 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001974811,0.0001320601,0.0001137339,0.0002577405,0.00004806852,0.0004468465,0.0008011948,0.00004253923,0.0005453901],"category_scores_gemma":[0.00002396469,0.0001198326,0.00004694235,0.0008081219,0.000007055554,0.0006389005,0.0003680105,0.0001967025,0.001468252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000182867,"about_ca_system_score_gemma":0.00007222444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001150619,"about_ca_topic_score_gemma":0.0003249726,"domain_scores_codex":[0.9987056,0.00005312648,0.0002408793,0.000506865,0.0002211232,0.000272423],"domain_scores_gemma":[0.9991037,0.0002683268,0.00001559847,0.0004731361,0.00002605665,0.0001132071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003070466,0.0004026157,0.002309703,0.0000452822,0.0001830225,0.0008542726,0.01204672,0.0265103,0.03852389,0.2464731,0.2198129,0.4528075],"study_design_scores_gemma":[0.0001397466,0.00009599904,0.001186501,0.0002515499,0.00001004891,0.00002215288,0.0001970345,0.869052,0.03733343,0.01316076,0.07815147,0.0003993307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01076599,0.0001609017,0.9757763,0.005484827,0.00205829,0.0002085709,0.000001999229,0.0004239006,0.005119251],"genre_scores_gemma":[0.4579614,0.0000132717,0.5359363,0.002278512,0.0001725303,0.00008083149,7.721338e-7,0.00002189163,0.003534523],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8425417,"threshold_uncertainty_score":0.9993092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03351599390332929,"score_gpt":0.309575272614337,"score_spread":0.2760592787110078,"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."}}