{"id":"W4392942780","doi":"10.1109/icmla58977.2023.00137","title":"Fake Review Detection Using Rating-Sentiment Inconsistency","year":2023,"lang":"en","type":"article","venue":"","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Sentiment analysis; Computer science; Artificial intelligence; Natural language processing; Information retrieval","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008232323,0.00003913849,0.00006627256,0.00005486704,0.0003630373,0.00005140164,0.00005239879,0.00002604883,0.001231728],"category_scores_gemma":[0.0003728661,0.00003373622,0.00003579521,0.0005437708,0.00002768795,0.0002605218,0.00001716906,0.00003413754,0.000659745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005638807,"about_ca_system_score_gemma":0.00008047722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004306764,"about_ca_topic_score_gemma":0.0004395486,"domain_scores_codex":[0.999316,0.00006716439,0.0001631706,0.00005615833,0.0002476496,0.0001499038],"domain_scores_gemma":[0.9997182,0.00002687162,0.0000582143,0.00007081107,0.00005290906,0.00007294928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008948809,0.00008127046,0.000733938,0.00112663,0.00006725438,0.000008044811,0.07605787,0.0001427515,0.004489243,0.03515466,0.1371341,0.7449953],"study_design_scores_gemma":[0.0005665105,0.00006968647,0.004850383,0.001459813,0.00007609878,0.000007542305,0.04457316,0.0130893,0.003273123,0.0013302,0.9300563,0.0006478499],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1881368,0.000695524,0.001853497,0.005477787,0.0008941494,0.0007628156,0.00000178027,0.0007151341,0.8014625],"genre_scores_gemma":[0.9742251,0.003941946,0.0005252856,0.003553701,0.0001435743,0.000002863329,0.000004917963,0.000006729032,0.0175959],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7929223,"threshold_uncertainty_score":0.9996813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09675258104084389,"score_gpt":0.4027484908998852,"score_spread":0.3059959098590413,"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."}}