{"id":"W6903379985","doi":"10.1109/tmc.2025.3587702","title":"A Generalizable Prompt-Based Prototypical Framework for CSI-Based Few-Shot and Cross-Domain Activity Recognition","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China; China Institute of Communications","keywords":"Activity recognition; Generalization; Representation (politics); Class (philosophy); Variety (cybernetics); Euclidean distance; Convolutional neural network; Facial recognition system; Pattern recognition (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":[0.0009893191,0.001132233,0.001132765,0.001000777,0.0004330123,0.0008889497,0.002596545,0.001102975,0.002478268],"category_scores_gemma":[0.002885138,0.0004394651,0.0008726693,0.001118204,0.0008965471,0.002464985,0.001968275,0.00143272,0.001037458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007511482,"about_ca_system_score_gemma":0.00141203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004403458,"about_ca_topic_score_gemma":0.005177399,"domain_scores_codex":[0.9991135,0.0001444091,0.00004178546,0.0004223705,0.0001853908,0.00009243001],"domain_scores_gemma":[0.9991981,0.0002052563,0.00008899433,0.0002042343,0.0002220067,0.00008133678],"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":[0.0006031757,0.0004351457,0.003107024,0.0003362808,0.000114721,0.0005013971,0.0004055716,0.2064819,0.03905971,0.02477508,0.009351416,0.7148287],"study_design_scores_gemma":[0.00001953729,0.0001243923,0.0007288054,0.00001184294,0.00001630327,0.000210362,0.00004855999,0.9781869,0.004705997,0.01284627,0.003075519,0.00002553244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005510357,0.0002340319,0.9913641,0.00007781334,0.00003978564,0.00008721232,0.0001739991,0.001809878,0.0007028831],"genre_scores_gemma":[0.3996043,0.0005644214,0.592228,0.0005103624,0.000143275,0.0005223154,0.001546805,0.000295302,0.004585198],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004403458,"threshold_uncertainty_score":0.008755684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02199191719109267,"score_gpt":0.2923259666850783,"score_spread":0.2703340494939856,"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."}}