{"id":"W4413318893","doi":"10.1109/access.2025.3600468","title":"Domain Adaptation for Retail Demand Prediction","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Institut de Valorisation des Données","keywords":"Domain adaptation; Adaptation (eye); Computer science; Domain (mathematical analysis); On demand; Artificial intelligence; Multimedia; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002717445,0.00006955775,0.000079786,0.0001201853,0.00009425236,0.000277264,0.001013845,0.00005071814,0.000001738148],"category_scores_gemma":[0.00003507493,0.00006828136,0.00002773922,0.0002955119,0.00001860613,0.001134594,0.0001338692,0.00004560222,0.00000271054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003584894,"about_ca_system_score_gemma":0.00005230995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002532235,"about_ca_topic_score_gemma":0.00002021845,"domain_scores_codex":[0.999333,0.00002621279,0.0001500123,0.0002616625,0.0001021434,0.0001269294],"domain_scores_gemma":[0.9993259,0.000092011,0.00005889051,0.0004292183,0.00007228117,0.00002166745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007610031,0.0001636771,0.009047693,0.0001910597,0.00009459528,0.000008210414,0.00116004,0.0004705863,0.004589896,0.2850363,0.1911988,0.5079631],"study_design_scores_gemma":[0.001421097,0.000281147,0.02847341,0.0003011108,0.00004769867,0.000008105456,0.00005710032,0.2593143,0.1002028,0.4516423,0.15779,0.0004609444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01061228,0.00002810703,0.9853523,0.0005556121,0.0005395979,0.0002730779,0.00002130573,0.0004455599,0.002172103],"genre_scores_gemma":[0.5904585,0.00001582809,0.4081553,0.0004596526,0.00009352808,0.0002756656,0.00003130096,0.000007901101,0.0005024268],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5798461,"threshold_uncertainty_score":0.2784433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04538142596367648,"score_gpt":0.3251650828672476,"score_spread":0.2797836569035711,"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."}}