{"id":"W4396797825","doi":"10.3390/electronics13101859","title":"Hidden Variable Models in Text Classification and Sentiment Analysis","year":2024,"lang":"en","type":"article","venue":"Electronics","topic":"Text and Document Classification Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Variable (mathematics); Sentiment analysis; Artificial intelligence; Computer science; Natural language processing; Pattern recognition (psychology); Mathematics","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":[0.0002355714,0.00008344884,0.0001076746,0.0004107915,0.00004216018,0.0002972014,0.0003217881,0.00006448886,0.00001438159],"category_scores_gemma":[0.000008052756,0.00007787528,0.00003271689,0.001793006,0.00002136154,0.0005390396,0.00009655157,0.0001479441,0.00002133116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001492035,"about_ca_system_score_gemma":0.00008950233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007399311,"about_ca_topic_score_gemma":0.00002031996,"domain_scores_codex":[0.9990842,0.00002357648,0.0001658594,0.0003620417,0.0001423913,0.0002219642],"domain_scores_gemma":[0.9995181,0.0000449941,0.00002968215,0.0003641174,0.00001865902,0.00002443824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.564768e-7,0.00001922958,0.000269198,0.00000654259,0.00005428254,0.000001192692,0.0001393073,0.0001927747,0.001056284,0.9267522,0.0003641265,0.07114407],"study_design_scores_gemma":[0.00006310749,0.00002405651,0.001379595,0.000006446661,0.00003450008,0.00000170414,0.00003165508,0.8094445,0.0008577866,0.1712777,0.01677321,0.0001057927],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02142111,0.01770261,0.9499596,0.005989891,0.00009144055,0.0001788974,0.000001471891,0.0008000248,0.003854928],"genre_scores_gemma":[0.9874503,0.0009678281,0.01046459,0.00004522949,0.000008170068,0.00003476071,0.000005445998,0.000005078607,0.001018614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9660292,"threshold_uncertainty_score":0.3175662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173114662248373,"score_gpt":0.2570866683851846,"score_spread":0.2397752021603473,"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."}}