{"id":"W4408930227","doi":"10.1145/3726864","title":"Enhancing Sequential Personalized Product Search with External Out-of-sequence Knowledge","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Information Systems","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Hôtel-Dieu de Montréal","funders":"National Natural Science Foundation of China","keywords":"Sequence (biology); Product (mathematics); Computer science; Information retrieval; Computational biology; Mathematics; Biology; Genetics","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":[0.001129314,0.001108491,0.001899021,0.001733924,0.0003994251,0.0008326799,0.001725009,0.001261099,0.001617132],"category_scores_gemma":[0.005350204,0.0006681739,0.0009551069,0.002449568,0.0004816706,0.003139045,0.001126107,0.001142059,0.001402345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005807832,"about_ca_system_score_gemma":0.00130066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009859724,"about_ca_topic_score_gemma":0.01729069,"domain_scores_codex":[0.9990191,0.0002442342,0.00006224192,0.0002997224,0.000295575,0.0000790749],"domain_scores_gemma":[0.9972256,0.001555587,0.0002067395,0.0005480515,0.0003534153,0.000110603],"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":[0.001044493,0.001113283,0.01148153,0.0004386157,0.0003650915,0.0004209962,0.0005517447,0.2694014,0.02016112,0.005713732,0.007376871,0.681931],"study_design_scores_gemma":[0.00002591717,0.0001360746,0.001463735,0.000009497676,0.00005836565,0.0002088634,0.00002806724,0.9907818,0.002444995,0.003384067,0.001439351,0.00001926085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1213941,0.002299061,0.8691382,0.0003455018,0.00006249399,0.0001175167,0.0005697012,0.003096205,0.002977117],"genre_scores_gemma":[0.7957942,0.001047757,0.1928308,0.0003667414,0.000173008,0.0001339322,0.002183264,0.0002469096,0.007223323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009859724,"threshold_uncertainty_score":0.01960462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04322400138114205,"score_gpt":0.3138986129252901,"score_spread":0.270674611544148,"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."}}