{"id":"W4413350112","doi":"10.1109/icde65448.2025.00169","title":"Enhancing Large-Scale Entity Alignment with Critical Structure and High-Quality Context","year":2025,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Natural Science Research of Jiangsu Higher Education Institutions of China; National Natural Science Foundation of China","keywords":"Computer science; Context (archaeology); Scale (ratio); Quality (philosophy); Geology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001105663,0.002161246,0.001317222,0.00235065,0.001078267,0.001522118,0.00213611,0.001641705,0.003643625],"category_scores_gemma":[0.006276284,0.0007547771,0.001466204,0.002871938,0.000672867,0.004701357,0.00287738,0.001616524,0.002840937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006942578,"about_ca_system_score_gemma":0.001495755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003532044,"about_ca_topic_score_gemma":0.008966761,"domain_scores_codex":[0.9985479,0.0003242788,0.00007362042,0.0006323845,0.0003208593,0.0001011501],"domain_scores_gemma":[0.997651,0.0008557013,0.0002260185,0.0007678332,0.0003590421,0.000140482],"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":[0.0005852904,0.0003918585,0.006065078,0.000728395,0.0002677791,0.0009037969,0.0006614546,0.1056926,0.04923461,0.01540332,0.02131961,0.7987463],"study_design_scores_gemma":[0.000148805,0.000257305,0.002650558,0.00005939285,0.0002116608,0.0008330053,0.0003870435,0.9015208,0.03811573,0.03086675,0.02488205,0.00006693683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03854369,0.001075136,0.9431308,0.0002956656,0.0001180617,0.0002342241,0.0007396313,0.01295078,0.002911871],"genre_scores_gemma":[0.2328701,0.0004336124,0.7543334,0.0003568514,0.00009798807,0.0002264674,0.005643072,0.00145318,0.004585349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003643625,"threshold_uncertainty_score":0.01218915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00964529877606188,"score_gpt":0.2835390011875726,"score_spread":0.2738937024115107,"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."}}