{"id":"W4408225310","doi":"10.1016/j.ins.2025.122067","title":"A group recommendation method based on automatically integrating members' preferences via taking advantages of LLM","year":2025,"lang":"en","type":"article","venue":"Information Sciences","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Science Foundation of Shandong Province","keywords":"Group (periodic table); Computer science; Information retrieval; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.002601933,0.0001249616,0.0001947787,0.0005977624,0.0002474312,0.0004019952,0.0008222956,0.00007762117,0.00003597302],"category_scores_gemma":[0.0002618228,0.00009181884,0.0000566431,0.00108463,0.0000686602,0.003155458,0.0001212763,0.0001368239,0.000005376659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004400545,"about_ca_system_score_gemma":0.0001133524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001795266,"about_ca_topic_score_gemma":0.00002639616,"domain_scores_codex":[0.9983797,0.0001827492,0.0006882281,0.0001871413,0.000386641,0.0001755225],"domain_scores_gemma":[0.998399,0.0005733834,0.0006046094,0.0002428333,0.0001471159,0.00003304242],"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":[0.000003354175,0.00003627686,0.0006997552,0.00007679591,0.000006615303,7.568119e-8,0.001018422,0.0003774539,0.0001424145,0.1408806,0.0004949433,0.8562633],"study_design_scores_gemma":[0.000139374,0.0002262273,0.001172367,0.0002538959,0.000003128029,0.000001610565,0.0005067804,0.9794858,0.004539382,0.00954325,0.004012446,0.0001157478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001010913,0.000004613736,0.9215892,0.001552003,0.0003194458,0.0002255294,0.00000207047,0.0002125268,0.07508368],"genre_scores_gemma":[0.603517,0.000001934848,0.3955773,0.0008557367,0.000005357895,0.00003044215,0.00000392208,9.787427e-7,0.000007294771],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9791083,"threshold_uncertainty_score":0.3876449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02514928117817871,"score_gpt":0.3498029883629197,"score_spread":0.324653707184741,"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."}}