{"id":"W4412378188","doi":"10.1145/3726302.3730369","title":"GENNEXT: The Next Generation of IR and Recommender Systems with Language Agents, Generative Models, and Conversational AI","year":2025,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Recommender system; Generative grammar; Natural language processing; Dialog system; Artificial intelligence; Human–computer interaction; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009426195,0.001135064,0.00129997,0.001069131,0.0009085044,0.004234025,0.004124333,0.002872244,0.0216572],"category_scores_gemma":[0.008469747,0.0009726199,0.001775079,0.001116744,0.001996796,0.00879981,0.00546866,0.004288149,0.006222728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275253,"about_ca_system_score_gemma":0.002012165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005604945,"about_ca_topic_score_gemma":0.006695362,"domain_scores_codex":[0.9971387,0.001643884,0.00008886988,0.0004679156,0.0004752851,0.0001853799],"domain_scores_gemma":[0.9952344,0.002432948,0.0001033797,0.0009856457,0.0006749642,0.0005687558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009908346,0.0004182167,0.001819793,0.001340043,0.0004005411,0.0003705559,0.002690938,0.01227699,0.009764956,0.2064003,0.1687548,0.5947719],"study_design_scores_gemma":[0.0002501353,0.000490681,0.0006556357,0.0004549393,0.0001531527,0.0003913709,0.0005280691,0.09931604,0.005025621,0.1334457,0.7591408,0.0001479531],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01054732,0.0215621,0.9046577,0.01450827,0.002620082,0.0005318856,0.001219093,0.01182937,0.03252432],"genre_scores_gemma":[0.07377774,0.008914922,0.8663575,0.005982545,0.001150338,0.0009276685,0.003757076,0.002384297,0.03674792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0216572,"threshold_uncertainty_score":0.07245052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07524424373046538,"score_gpt":0.2804865239088263,"score_spread":0.2052422801783609,"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."}}