{"id":"W7112133878","doi":"","title":"A Sampling-Based Domain Generalization Study with Diffusion Generative Models","year":2025,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Generalization; Domain (mathematical analysis); Diffusion; Feature (linguistics); Generative grammar; Bounded function; Generative model","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":[0.006702194,0.0008037461,0.001977928,0.001769514,0.001181627,0.001924565,0.002668705,0.002046302,0.003330746],"category_scores_gemma":[0.03043975,0.0008853424,0.00243522,0.00191507,0.002182168,0.00418917,0.002483743,0.003131358,0.0003046932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002330257,"about_ca_system_score_gemma":0.001101584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01528462,"about_ca_topic_score_gemma":0.00714098,"domain_scores_codex":[0.9986223,0.0007401675,0.0000456112,0.0002819469,0.0001721541,0.000137867],"domain_scores_gemma":[0.9667832,0.02734756,0.001359184,0.001898263,0.001658531,0.0009532711],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003382124,0.0001638468,0.004556141,0.0003084055,0.0001667628,0.0004112715,0.001079564,0.6361979,0.003153157,0.3198057,0.004209681,0.02960948],"study_design_scores_gemma":[0.00001045297,0.00002403919,0.0004285602,0.00001600931,0.00002290484,0.00006381276,0.00006262143,0.961245,0.0002181087,0.03746144,0.0004318277,0.00001525501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.197206,0.002146753,0.7923983,0.001682904,0.0001068784,0.0001126022,0.0001701219,0.0003484428,0.005828013],"genre_scores_gemma":[0.9228011,0.002095715,0.0674462,0.0003180044,0.000292223,0.0001203003,0.0004162363,0.0002605894,0.006249733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01528462,"threshold_uncertainty_score":0.03544503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01672036323836504,"score_gpt":0.2548562814055518,"score_spread":0.2381359181671867,"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."}}