{"id":"W2015949613","doi":"10.1109/glocom.2006.559","title":"SPC05-4: Successively Structured Gaussian CEO Problem","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Gaussian; Rate distortion; Relay; Mathematical optimization; Rate–distortion theory; Fusion center; Coding (social sciences); Computer science; Dirty paper coding; Distortion (music); Mathematics; Topology (electrical circuits); Beamforming; Bandwidth (computing); Telecommunications; Wireless; Statistics; MIMO; Combinatorics; Precoding; Cognitive radio","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008814756,0.0001799612,0.0001716183,0.0000724452,0.0002003566,0.0003978024,0.0006590555,0.00009704371,0.00009138934],"category_scores_gemma":[0.000005194435,0.0001596852,0.00008676258,0.0005683349,0.00003908805,0.0003556859,0.0001438228,0.0001581452,0.0001380906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005801788,"about_ca_system_score_gemma":0.00004204753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003630194,"about_ca_topic_score_gemma":0.0001616174,"domain_scores_codex":[0.9985732,0.00004384555,0.000270927,0.0004225393,0.000276235,0.0004132129],"domain_scores_gemma":[0.9992077,0.00002135498,0.0001261017,0.0004528763,0.00007851114,0.0001134637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004307312,0.000339349,0.004260514,0.00004629642,0.00008229536,0.0003078967,0.0001628796,0.01235228,0.001147212,0.3724457,0.2291409,0.3796715],"study_design_scores_gemma":[0.002164762,0.0002318788,0.1455023,0.00005548032,0.00002702207,0.0003224596,0.00004209439,0.1477989,0.006183759,0.1148136,0.5814102,0.001447633],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009292767,0.0002123252,0.9484221,0.001580157,0.001577518,0.0002679372,0.00004181491,0.0008230497,0.03778238],"genre_scores_gemma":[0.9493247,0.000005081487,0.04855915,0.0002889709,0.000396858,0.00001016386,0.00003086269,0.00001297654,0.001371246],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9400319,"threshold_uncertainty_score":0.6511773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004476794363137375,"score_gpt":0.199994323651762,"score_spread":0.1955175292886246,"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."}}