{"id":"W4402192705","doi":"10.1002/cjs.11831","title":"Distributed learning for kernel mode–based regression","year":2024,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Kernel (algebra); Mode (computer interface); Kernel regression; Regression; Artificial intelligence; Machine learning; Statistics; Mathematics; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00335258,0.0007164078,0.001108678,0.0005045956,0.0002858655,0.00081487,0.002107208,0.001002919,0.001977212],"category_scores_gemma":[0.01239176,0.0004505599,0.0006785406,0.0007039204,0.001139762,0.001362442,0.001857146,0.0018911,0.0006966335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005850479,"about_ca_system_score_gemma":0.0008537304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001372495,"about_ca_topic_score_gemma":0.001032867,"domain_scores_codex":[0.9985471,0.0006956424,0.00004815973,0.0003210066,0.0003005498,0.00008746638],"domain_scores_gemma":[0.995378,0.002647913,0.0004136194,0.0007314018,0.0007118012,0.0001172365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001560254,0.00008993068,0.001392245,0.0001020337,0.00008390923,0.00009582268,0.00009318505,0.8433838,0.005489525,0.0486179,0.00228649,0.09820921],"study_design_scores_gemma":[0.000004336277,0.00001181999,0.00006861713,0.000002391162,0.000001847519,0.000008133552,0.000002444286,0.9938006,0.0003510852,0.005536457,0.0002085404,0.000003785712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003440558,0.0000600978,0.9961209,0.00006558212,0.00001159323,0.00000831003,0.00001380595,0.0001059728,0.0001731942],"genre_scores_gemma":[0.6022223,0.000382182,0.3912401,0.000220343,0.0001788755,0.0002542247,0.000330792,0.0002784334,0.004892676],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00335258,"threshold_uncertainty_score":0.01773036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202203004559688,"score_gpt":0.2254015715348227,"score_spread":0.2133795414892258,"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."}}