{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008474201,0.000476009,0.0005595146,0.0005428583,0.0007598639,0.0005888731,0.001265604,0.0002981869,0.0002711141],"category_scores_gemma":[0.00003440172,0.0004383304,0.0003968323,0.0009511538,0.0001123969,0.0005781436,0.0004871093,0.0003282887,0.00007951182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003477659,"about_ca_system_score_gemma":0.0004156461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002728499,"about_ca_topic_score_gemma":0.0001933203,"domain_scores_codex":[0.9966099,0.0003159261,0.000948646,0.001132045,0.0002814636,0.000712009],"domain_scores_gemma":[0.9974166,0.0005163103,0.0003025043,0.001217087,0.0003728627,0.0001746072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005981853,0.0003148202,0.0000299841,0.00003851991,0.0001897356,0.000005561082,0.0002567684,0.000003581212,0.00003277662,0.7129193,0.1533609,0.1327882],"study_design_scores_gemma":[0.002137522,0.001298599,0.00009044192,0.0007489768,0.00009902062,0.00001399143,0.000219006,0.1544128,0.01594864,0.1243842,0.6998295,0.0008173418],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001417082,0.0001134659,0.8849617,0.02589834,0.004642342,0.001947229,0.00009223889,0.0004053903,0.08179756],"genre_scores_gemma":[0.6780325,0.0002683116,0.2848203,0.004364564,0.0004424371,0.0007457088,0.00004320062,0.00004012659,0.0312428],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6778908,"threshold_uncertainty_score":0.9998068,"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."}}