{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003020928,0.0009003287,0.0009022764,0.00173992,0.0006935906,0.001784941,0.001575047,0.00140956,0.002823598],"category_scores_gemma":[0.008216184,0.0004967111,0.001273141,0.001966267,0.001305512,0.002391638,0.0009852265,0.002223886,0.001025582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001194315,"about_ca_system_score_gemma":0.0008795795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007109591,"about_ca_topic_score_gemma":0.007236863,"domain_scores_codex":[0.9982353,0.0009375955,0.00007528739,0.000376367,0.0002473508,0.0001279965],"domain_scores_gemma":[0.9966008,0.002543198,0.0002870983,0.0002380539,0.0002613048,0.00006961728],"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":[0.0001929954,0.0001459218,0.005225582,0.0003291373,0.0003343076,0.000218051,0.0005861201,0.5231841,0.003123624,0.2396936,0.007040006,0.2199266],"study_design_scores_gemma":[0.000005216083,0.000009291404,0.0004635567,0.00001499097,0.00001297134,0.00001468861,0.00002216944,0.934357,0.0002948782,0.06335469,0.001439134,0.00001136187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01366363,0.0009473892,0.9819405,0.0009533321,0.0001504465,0.00004749911,0.0002925611,0.0004262853,0.001578419],"genre_scores_gemma":[0.5708702,0.001842926,0.415919,0.0005250965,0.0006656486,0.0003032384,0.001555531,0.0003528375,0.0079656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007109591,"threshold_uncertainty_score":0.01597637,"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."}}