{"id":"W4412130177","doi":"10.1109/icmc60390.2024.00016","title":"Meta Learning Based Adaptive Cooperative Perception in Nonstationary Vehicular Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Brain Tumor Detection and Classification","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Perception; Artificial intelligence; Psychology","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":[0.001153457,0.0008545023,0.0009539047,0.0003930649,0.0003841223,0.0009261766,0.001442846,0.0007636277,0.0006439151],"category_scores_gemma":[0.002488344,0.0005407719,0.0006088504,0.0003647755,0.0009326311,0.001002103,0.001150257,0.001207518,0.0001283863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008909366,"about_ca_system_score_gemma":0.0007758274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007633955,"about_ca_topic_score_gemma":0.005017737,"domain_scores_codex":[0.9995547,0.000130842,0.00002105819,0.0001134399,0.0000774908,0.0001024608],"domain_scores_gemma":[0.9986485,0.0007695801,0.0002145965,0.00008650134,0.0001917557,0.00008905622],"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":[0.00002920913,0.00001412578,0.0003013504,0.00001310417,0.00002041011,0.0000324746,0.00003885874,0.9886685,0.00100425,0.002005099,0.0001048963,0.007767754],"study_design_scores_gemma":[0.00000179372,0.00001215568,0.00004089245,0.000001016289,0.000002497941,0.000003241958,0.00000402233,0.9991303,0.0001422557,0.0006238346,0.00003585276,0.000002087026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07099911,0.0003333416,0.9264416,0.0001808733,0.00003545763,0.00002612525,0.0000244192,0.0002783389,0.001680712],"genre_scores_gemma":[0.9875335,0.0000737051,0.01164493,0.00003909491,0.00001088448,0.00003045286,0.00001702367,0.00001558026,0.0006348266],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007633955,"threshold_uncertainty_score":0.01517904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07028991125872669,"score_gpt":0.2815762323477327,"score_spread":0.211286321089006,"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."}}