{"id":"W4407654895","doi":"10.1145/3718488","title":"Balancing Embedding Spectrum for Recommendation","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Recommender Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Embedding; Spectrum (functional analysis); Artificial intelligence; Physics","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":[0.0009528586,0.0003182808,0.0004350453,0.0005918039,0.0005821033,0.0004809943,0.001153193,0.000183821,0.00002767656],"category_scores_gemma":[0.00003544611,0.0003106844,0.0002327512,0.0006482645,0.00001495787,0.0006123244,0.00003563155,0.0002906815,0.00002109596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377813,"about_ca_system_score_gemma":0.0000844943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001872828,"about_ca_topic_score_gemma":0.00004218187,"domain_scores_codex":[0.9976845,0.0002091873,0.0007109169,0.0007156517,0.0001735132,0.000506186],"domain_scores_gemma":[0.9976428,0.0006795718,0.0002014198,0.001276522,0.0001001688,0.00009957986],"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":[0.00007000907,0.0006583611,0.0002687388,0.000745254,0.000749342,0.000003633015,0.00102578,0.0019426,0.000404493,0.1023122,0.1239651,0.7678545],"study_design_scores_gemma":[0.002105588,0.0004617247,0.0001169881,0.0007484464,0.00007383178,0.00005351555,0.0009579018,0.2291335,0.01054819,0.02342192,0.731346,0.001032416],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00006529279,0.00009018782,0.9683535,0.01802962,0.005733314,0.001162201,0.00002257253,0.0008668066,0.005676585],"genre_scores_gemma":[0.9163582,0.00008603506,0.07771216,0.001510135,0.0001598196,0.00134462,0.00002373854,0.00004318091,0.002762098],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9162929,"threshold_uncertainty_score":0.9999346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706613366870131,"score_gpt":0.3083818690799667,"score_spread":0.2813157354112654,"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."}}