{"id":"W4392904594","doi":"10.1109/icassp48485.2024.10446383","title":"Distributed Vector Approximate Message Passing","year":2024,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Message passing; Computer science; Noise (video); Class (philosophy); SIGNAL (programming language); Algorithm; Distributed algorithm; Theoretical computer science; Distributed computing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001720288,0.0009104277,0.00134441,0.0007406866,0.0005050167,0.001546651,0.001431313,0.001350964,0.0021712],"category_scores_gemma":[0.007597861,0.0003867563,0.0006323569,0.001284156,0.001180412,0.002605353,0.00152942,0.00117187,0.0005107151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009614528,"about_ca_system_score_gemma":0.0009541342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001902653,"about_ca_topic_score_gemma":0.001129559,"domain_scores_codex":[0.9983799,0.0006299252,0.00007754373,0.0003231513,0.000439994,0.0001493889],"domain_scores_gemma":[0.9969074,0.00195935,0.00024871,0.0003933834,0.0004242279,0.00006682892],"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":[0.000159861,0.00002735286,0.0003620317,0.0001114987,0.00006006171,0.00006275276,0.0001171577,0.8181655,0.001842998,0.101106,0.001724696,0.07626013],"study_design_scores_gemma":[0.00001501507,0.00003157037,0.00003068317,0.000005909564,0.000006596443,0.0000196921,0.00001051629,0.9728394,0.0007030234,0.02498309,0.001348568,0.000006039386],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002374082,0.0001636967,0.9964433,0.00009318,0.00003542452,0.00001343704,0.00001629503,0.0001517086,0.0007088582],"genre_scores_gemma":[0.5709096,0.0009214662,0.4207152,0.0003139381,0.0002382227,0.0002657771,0.0002341445,0.0001092183,0.006292455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0021712,"threshold_uncertainty_score":0.009097874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01151641395596332,"score_gpt":0.2350194234579463,"score_spread":0.223503009501983,"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."}}