{"id":"W4392945256","doi":"10.1109/cac59555.2023.10451936","title":"Improving Knowledge Graph-based BERT Pre-Training Through Entity Hot Partition and Adapter Fusion","year":2023,"lang":"en","type":"article","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Adapter (computing); Computer science; Knowledge graph; Graph; Partition (number theory); Artificial intelligence; Theoretical computer science; Operating system; Mathematics","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":[0.000957112,0.001856061,0.001154933,0.001765711,0.0007999833,0.0009459178,0.002349003,0.001654655,0.002880889],"category_scores_gemma":[0.004750684,0.0005934126,0.001048008,0.001567301,0.0007976969,0.004656511,0.002782193,0.002081237,0.001499137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008997529,"about_ca_system_score_gemma":0.0009362949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007579407,"about_ca_topic_score_gemma":0.01302528,"domain_scores_codex":[0.9992944,0.0001407046,0.00003670026,0.0002506934,0.0001522614,0.0001251988],"domain_scores_gemma":[0.998245,0.0006876813,0.0001684907,0.0004628857,0.0003277254,0.0001082434],"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":[0.0005886659,0.0006187275,0.0140609,0.0002761253,0.0001841437,0.0004299744,0.0004649735,0.4169399,0.01967174,0.007656225,0.01370906,0.5253996],"study_design_scores_gemma":[0.000009296204,0.00007878875,0.001189069,0.00001271717,0.00002557172,0.00006585979,0.0001017687,0.9869752,0.005468911,0.004696239,0.001363997,0.00001257335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.186181,0.0006673509,0.7948276,0.0005166286,0.0001124467,0.0002343927,0.0008924379,0.01246941,0.004098656],"genre_scores_gemma":[0.8360385,0.0002602875,0.1528576,0.0003505766,0.00005660539,0.0001969621,0.005580546,0.0003909832,0.004267897],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007579407,"threshold_uncertainty_score":0.01507062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08748572990892053,"score_gpt":0.3015311431381947,"score_spread":0.2140454132292742,"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."}}