{"id":"W4401667261","doi":"10.54097/f09tdt83","title":"Adaptive Neural Network Architectures for Cross-Domain Generalization","year":2024,"lang":"en","type":"article","venue":"Jisuanji shenghuojia.","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Modular design; Robustness (evolution); Adaptability; Artificial intelligence; Artificial neural network; Benchmark (surveying); Machine learning; Domain (mathematical analysis)","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":[0.001358496,0.001254715,0.0009853612,0.0007838928,0.0004298929,0.0007670486,0.001819353,0.001203762,0.001330921],"category_scores_gemma":[0.002990779,0.000428016,0.0009518638,0.0008094839,0.0007954547,0.001832663,0.001522343,0.00199217,0.0004599311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009158371,"about_ca_system_score_gemma":0.0006086389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00376258,"about_ca_topic_score_gemma":0.003298366,"domain_scores_codex":[0.9995574,0.000106162,0.00003035518,0.0001876459,0.00007483253,0.00004350992],"domain_scores_gemma":[0.9991566,0.0003309709,0.0001061967,0.0001905214,0.0001782796,0.00003737793],"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":[0.00007186912,0.00009341962,0.001143262,0.00007506693,0.0001350723,0.00009019997,0.00008331965,0.7802943,0.007564129,0.007230053,0.001864983,0.2013542],"study_design_scores_gemma":[0.000002554205,0.00001851765,0.0001391207,0.000003975701,0.000009547269,0.00001538021,0.000005509381,0.9943874,0.0008297632,0.004287154,0.0002960092,0.000005055307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0365409,0.001109487,0.9591275,0.0002797059,0.00006892817,0.00004767531,0.00005794147,0.0009475822,0.001820219],"genre_scores_gemma":[0.8264164,0.0008154029,0.168176,0.000367927,0.0001066202,0.0001559633,0.0003600702,0.0001250212,0.00347657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00376258,"threshold_uncertainty_score":0.007481337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02671408393354187,"score_gpt":0.3048156728266197,"score_spread":0.2781015888930778,"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."}}