{"id":"W4293863311","doi":"10.1109/siu55565.2022.9864851","title":"Automatic Keyword Extraction From Dialogue Text","year":2022,"lang":"en","type":"article","venue":"2022 30th Signal Processing and Communications Applications Conference (SIU)","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Computer science; Keyword extraction; Dialog box; Recall; Word (group theory); Natural language processing; Precision and recall; Information retrieval; Process (computing); Artificial intelligence; Customer service; Service (business); World Wide Web; Linguistics","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":[0.001118864,0.001490005,0.001279618,0.005000246,0.0007055044,0.001403762,0.0006564389,0.0008014677,0.005273897],"category_scores_gemma":[0.006164108,0.0003268665,0.0007601778,0.002734729,0.0002700512,0.001876101,0.0008948096,0.0004597512,0.008960374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004123262,"about_ca_system_score_gemma":0.001084162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257272,"about_ca_topic_score_gemma":0.0012241,"domain_scores_codex":[0.9978324,0.0004886772,0.0003899022,0.0004925539,0.0005969137,0.0001995372],"domain_scores_gemma":[0.9949887,0.001618474,0.0003361698,0.0003559971,0.00256463,0.0001359324],"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":[0.0008693155,0.0001142608,0.004972161,0.002634346,0.00008919257,0.001018757,0.001465364,0.001471203,0.3614176,0.002244602,0.01738705,0.6063161],"study_design_scores_gemma":[0.0002333615,0.0009663859,0.02936738,0.0004994653,0.0003705911,0.006241049,0.003734704,0.109958,0.6610289,0.009053927,0.1781739,0.0003724391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1684655,0.005114078,0.768657,0.0005564686,0.000639866,0.001353621,0.01755326,0.0263548,0.0113054],"genre_scores_gemma":[0.3096552,0.001464702,0.6540188,0.0001722512,0.0002534573,0.0009554672,0.02228783,0.001155979,0.01003633],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005273897,"threshold_uncertainty_score":0.01764297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02983636651314105,"score_gpt":0.3031218038835432,"score_spread":0.2732854373704022,"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."}}