{"id":"W4281492733","doi":"10.36227/techrxiv.19808446","title":"Performance Evaluation of Few-shot Learning-based System Identification","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Machine Learning and ELM","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Identification (biology); Computer science; Bounded function; Artificial intelligence; White noise; Noise (video); Algorithm; System identification; Machine learning; Norm (philosophy); Data mining; Mathematics; Image (mathematics)","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":[0.005501977,0.001276012,0.001907063,0.00110276,0.0007473775,0.001325152,0.001174612,0.002054228,0.001200813],"category_scores_gemma":[0.0195965,0.0002460231,0.0004619675,0.0004409546,0.001128573,0.001837654,0.001950792,0.001132909,0.0004802444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009401346,"about_ca_system_score_gemma":0.0008626768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002707134,"about_ca_topic_score_gemma":0.001394116,"domain_scores_codex":[0.9966396,0.001265605,0.0002086851,0.0006299856,0.001032622,0.0002235693],"domain_scores_gemma":[0.9905736,0.006281528,0.0005802727,0.0007544417,0.00143055,0.0003796217],"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":[0.001553367,0.0003984966,0.005317785,0.0006452189,0.0003374944,0.0001986074,0.0002003985,0.7411557,0.01413487,0.003298562,0.001110976,0.2316486],"study_design_scores_gemma":[0.00001140633,0.0003491155,0.00156669,0.00001604171,0.00002695,0.000121429,0.00003954203,0.9904662,0.006361451,0.0008412219,0.0001735145,0.00002635577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2320463,0.004084479,0.7561352,0.0003976692,0.0002151444,0.0001542229,0.000131089,0.002145632,0.004690257],"genre_scores_gemma":[0.9591948,0.0002628545,0.03906435,0.00009904584,0.00003957002,0.00004877009,0.0002397926,0.00007848514,0.000972433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005501977,"threshold_uncertainty_score":0.02909756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04651296599958438,"score_gpt":0.3118335274483927,"score_spread":0.2653205614488083,"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."}}