{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002236535,0.0009353163,0.001214436,0.0008701435,0.0008493621,0.001080423,0.001739036,0.001451564,0.00350493],"category_scores_gemma":[0.009821524,0.0005391953,0.0005902003,0.001115106,0.0009281583,0.003485012,0.002208169,0.001904922,0.001947868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008720903,"about_ca_system_score_gemma":0.0009753244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002590691,"about_ca_topic_score_gemma":0.004826817,"domain_scores_codex":[0.9978592,0.0007125105,0.00008700161,0.0005947205,0.0005965115,0.0001500283],"domain_scores_gemma":[0.9970337,0.001224414,0.0001916075,0.0009073908,0.0005091502,0.0001336792],"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":[0.000487941,0.0005623318,0.003510305,0.0001986382,0.0001164136,0.0001148197,0.0004192678,0.241985,0.0206496,0.04343733,0.01038086,0.6781375],"study_design_scores_gemma":[0.00003035655,0.0000799511,0.0004452881,0.00001324703,0.00001445023,0.00008036981,0.00005830212,0.9670452,0.00332386,0.02619632,0.002693963,0.00001869068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02491557,0.0003290989,0.9712213,0.0002423654,0.00003972101,0.00006414232,0.00007176869,0.001058456,0.002057629],"genre_scores_gemma":[0.5845034,0.0003111163,0.4089459,0.0004841374,0.0001267148,0.0002237506,0.0003989661,0.0002824074,0.004723538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00350493,"threshold_uncertainty_score":0.01182806,"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."}}