{"id":"W4410901013","doi":"10.1145/3742421","title":"Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives","year":2025,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University; Royal Bank of Canada; Vector Institute","funders":"","keywords":"Computer science; Recommender system; Data science; World Wide Web","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01624782,0.0007910727,0.003825555,0.0004857043,0.0001394978,0.0001555567,0.002941891,0.0004732681,0.000001783006],"category_scores_gemma":[0.0007731548,0.0006385777,0.000418234,0.001024694,0.00007297602,0.0001520796,0.001474927,0.0006413624,0.000002248225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001294181,"about_ca_system_score_gemma":0.0005294998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005267842,"about_ca_topic_score_gemma":0.00008913151,"domain_scores_codex":[0.9839303,0.01233098,0.001500979,0.00141437,0.0003498305,0.0004735684],"domain_scores_gemma":[0.9908112,0.004453036,0.001376141,0.002836554,0.0004041042,0.0001189472],"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":[3.269649e-7,0.00006585995,0.00001471924,0.1252536,0.0001735528,0.000001903536,0.0001501139,2.920643e-7,1.453937e-9,0.002665071,0.003520902,0.8681537],"study_design_scores_gemma":[0.0001933562,0.0001166224,0.0006523047,0.1613674,0.000192507,0.00004364281,0.000103252,0.0005983039,1.41247e-7,0.00008665492,0.8356767,0.0009691642],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[8.21021e-8,0.9410304,0.0547927,0.0005362318,0.000859599,0.001537099,0.00005126813,0.0003207573,0.000871884],"genre_scores_gemma":[0.00004611293,0.990792,0.0086596,0.00004561443,0.0001880191,0.0000889107,0.0001026815,0.00004590184,0.00003114504],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8671845,"threshold_uncertainty_score":0.9996065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2073355772120554,"score_gpt":0.352680536825045,"score_spread":0.1453449596129896,"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."}}