{"id":"W4392608406","doi":"10.33137/ijournal.v9i1.42237","title":"Conversational Breakdown Detector for a Motivational Interviewing Conversational Agent","year":2023,"lang":"en","type":"article","venue":"The iJournal Student Journal of the Faculty of Information","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interview; Motivational interviewing; Psychology; Detector; Computer science; Sociology; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002201605,0.0001119881,0.0001739917,0.0001911973,0.0003099075,0.0001578929,0.001493244,0.00003859781,0.000020751],"category_scores_gemma":[0.0003028997,0.00006370171,0.0002976208,0.0003286108,0.00005198198,0.001540309,0.0002602371,0.0002218943,0.00001394174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001793177,"about_ca_system_score_gemma":0.0001935142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007592179,"about_ca_topic_score_gemma":0.000001773448,"domain_scores_codex":[0.9974799,0.00008525338,0.0009725999,0.00006348815,0.001228412,0.0001704092],"domain_scores_gemma":[0.9972087,0.0002781678,0.00140764,0.0001857593,0.0008642661,0.00005546283],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0004205977,0.0003028902,0.04642957,0.000352513,0.002217747,0.000005868735,0.1133154,0.5872749,0.003773981,0.09766878,0.04462799,0.1036097],"study_design_scores_gemma":[0.005297224,0.0003104314,0.5574594,0.0005343712,0.0001312003,0.0004645459,0.005423702,0.3944493,0.003654441,0.01669865,0.01520308,0.0003737433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3704734,0.00002641307,0.6153494,0.0124818,0.001260021,0.0002949126,0.00002626503,0.00001904766,0.00006868476],"genre_scores_gemma":[0.992575,0.0000157375,0.006602309,0.0005338081,0.0001973826,0.000006285905,0.000009374762,0.000004106689,0.00005594157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6221016,"threshold_uncertainty_score":0.2774844,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04879673560062339,"score_gpt":0.3038524488520255,"score_spread":0.2550557132514021,"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."}}