{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002441778,0.0007312455,0.00100695,0.001963407,0.0002542553,0.001294407,0.0006376153,0.0008045806,0.0006231807],"category_scores_gemma":[0.0134939,0.0002373251,0.0005147225,0.0008346007,0.0002706208,0.001509715,0.0006301948,0.00078231,0.0006230064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006586042,"about_ca_system_score_gemma":0.0004360546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001968354,"about_ca_topic_score_gemma":0.001966082,"domain_scores_codex":[0.9979776,0.0004955146,0.0001907622,0.0004435102,0.0007568821,0.0001357982],"domain_scores_gemma":[0.9901415,0.003267247,0.003028077,0.0008433555,0.002495634,0.0002243082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002483621,0.0007240315,0.2412648,0.0007198614,0.0007793729,0.001248496,0.0008761134,0.05433585,0.05633167,0.002733697,0.008863177,0.6296393],"study_design_scores_gemma":[0.00002749834,0.0003807162,0.04386212,0.00003419258,0.0001279601,0.0006834415,0.0001368729,0.9263758,0.02575133,0.001203379,0.001363728,0.00005293412],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8605266,0.001273062,0.1304625,0.0005544287,0.0001295562,0.000218279,0.0006544608,0.001815776,0.004365488],"genre_scores_gemma":[0.9815014,0.0001258348,0.01696136,0.00004939282,0.00004333637,0.00002261497,0.0004075875,0.00002715386,0.0008614178],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002441778,"threshold_uncertainty_score":0.01291353,"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."}}