{"id":"W4417003889","doi":"10.1109/uemcon67449.2025.11267593","title":"Adaptive Weighted Loss for Sequential Recommendations on Sparse Domains","year":2025,"lang":"","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kindercare Pediatrics","funders":"","keywords":"Weighting; Stability (learning theory); Key (lock); Convergence (economics); Domain (mathematical analysis); Function (biology); Weight function","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":[0.004255878,0.0014187,0.002125185,0.001234537,0.0006473381,0.001473683,0.002593132,0.001695182,0.002698676],"category_scores_gemma":[0.01186901,0.0006853676,0.0008472771,0.001573991,0.0008978007,0.003713782,0.001698641,0.002392234,0.001668876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422187,"about_ca_system_score_gemma":0.001456193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006701111,"about_ca_topic_score_gemma":0.009613941,"domain_scores_codex":[0.9980448,0.0007054458,0.0001124302,0.0004467895,0.0005173826,0.0001729965],"domain_scores_gemma":[0.9949476,0.003077011,0.0002862276,0.0008471251,0.0006392201,0.0002029035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00047582,0.0004602594,0.002903649,0.0002960813,0.0001437953,0.0001297929,0.0001414338,0.6675137,0.004086804,0.01874917,0.01118148,0.2939179],"study_design_scores_gemma":[0.00002328096,0.00007074214,0.0001924943,0.00001057346,0.00001052871,0.00003489049,0.00001492636,0.9910471,0.000468436,0.007296046,0.0008222444,0.000008683057],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03347182,0.001024163,0.9611198,0.0004939149,0.00008454538,0.000135656,0.0002633743,0.001247609,0.002158981],"genre_scores_gemma":[0.5776452,0.0009036915,0.4095799,0.0005436136,0.0002428412,0.0003758312,0.00135644,0.0002753458,0.009077157],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006701111,"threshold_uncertainty_score":0.02250749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05026966653022254,"score_gpt":0.3209246303631285,"score_spread":0.270654963832906,"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."}}