{"id":"W3210819377","doi":"10.1109/tai.2021.3120043","title":"Smoothed Generalized Dirichlet: A Novel Count-Data Model for Detecting Emotional States","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Artificial Intelligence","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dirichlet distribution; Burstiness; Count data; Generalized Dirichlet distribution; Mathematics; Computer science; Hierarchical Dirichlet process; Applied mathematics; Multinomial distribution; Cluster analysis; Algorithm; Artificial intelligence; Statistics; Dirichlet series; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00520467,0.001517363,0.002534986,0.003457422,0.001137788,0.002998149,0.004980851,0.002263204,0.00394162],"category_scores_gemma":[0.02287178,0.001113437,0.002318079,0.004129085,0.001803363,0.006058665,0.002531693,0.003166581,0.001599323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001665612,"about_ca_system_score_gemma":0.00125074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005260356,"about_ca_topic_score_gemma":0.006323882,"domain_scores_codex":[0.99567,0.001928875,0.0002716169,0.001089162,0.0007581327,0.0002823542],"domain_scores_gemma":[0.9913588,0.005843722,0.0006345169,0.001050888,0.0009008669,0.0002112147],"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":[0.001012385,0.0003338887,0.0123052,0.000710016,0.0005588939,0.0005682487,0.001576805,0.4237962,0.007145305,0.1983247,0.0141709,0.3394975],"study_design_scores_gemma":[0.00001567126,0.00002525221,0.0005735969,0.00002494326,0.00002397814,0.00008712392,0.0000611729,0.9314457,0.0006646499,0.06496044,0.002087262,0.00003029454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008622046,0.0003847737,0.9889685,0.0003018913,0.00009010302,0.00007364529,0.0004117264,0.0004842923,0.0006630292],"genre_scores_gemma":[0.4321586,0.001362263,0.553748,0.0006518534,0.0006456837,0.0009209907,0.003438066,0.0005105662,0.006564055],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005260356,"threshold_uncertainty_score":0.02752519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1619633829215689,"score_gpt":0.3418206002684397,"score_spread":0.1798572173468707,"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."}}