{"id":"W4406825368","doi":"10.18280/mmep.120123","title":"Sarcasm Detection an Explainable AI Approach for Reddit Political Text","year":2025,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Topic Modeling","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sarcasm; Politics; Artificial intelligence; Natural language processing; Computer science; History; Psychology; Political science; Irony; Linguistics; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081499,0.0007896699,0.0004021228,0.001531814,0.0004293173,0.001046793,0.0007767962,0.0006411548,0.003590991],"category_scores_gemma":[0.002758656,0.0001875635,0.0007028834,0.0005651604,0.0002278112,0.001160494,0.0004881372,0.0009623092,0.001945013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000473993,"about_ca_system_score_gemma":0.0004375709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001419259,"about_ca_topic_score_gemma":0.002253673,"domain_scores_codex":[0.9994093,0.000134507,0.0000513165,0.0001858561,0.0001747053,0.0000443406],"domain_scores_gemma":[0.9986896,0.0005736413,0.0001882721,0.0001070014,0.0004044821,0.00003712774],"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":[0.0003776968,0.0004466418,0.01549997,0.000638077,0.0002249968,0.0005784453,0.001768156,0.008724503,0.0581438,0.004199447,0.01986163,0.8895366],"study_design_scores_gemma":[0.00005003513,0.0005803134,0.03498699,0.0001466632,0.0002271697,0.0007401409,0.001358264,0.8643706,0.05750404,0.01175608,0.0281902,0.00008952648],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2055979,0.001187364,0.750683,0.002857039,0.0004926472,0.001066322,0.003379238,0.01854233,0.01619417],"genre_scores_gemma":[0.7093409,0.0005915973,0.2699228,0.0004272494,0.0002113963,0.0004720488,0.004649826,0.0002368035,0.01414724],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003590991,"threshold_uncertainty_score":0.01201308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02510065594761669,"score_gpt":0.2339263670081814,"score_spread":0.2088257110605647,"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."}}