{"id":"W2164638100","doi":"10.1109/glocom.2005.1577871","title":"Performance of the successive coding strategy in the CEO problem","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Wireless sensor network; Distortion (music); Rate distortion; Gaussian; Coding (social sciences); Upper and lower bounds; Rate–distortion theory; Computer science; Algorithm; Mathematics; Mathematical optimization; Statistics; Telecommunications; Computer network; Physics","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":[0.004828281,0.001489016,0.001784854,0.00081006,0.0006513874,0.001772097,0.001420671,0.001751839,0.002744953],"category_scores_gemma":[0.02077602,0.0003805592,0.0006479902,0.000896481,0.002074937,0.002719884,0.002528256,0.00145332,0.0003653421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00168745,"about_ca_system_score_gemma":0.003105529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004578239,"about_ca_topic_score_gemma":0.001944763,"domain_scores_codex":[0.9976442,0.001121603,0.00006517339,0.0002458755,0.0004191609,0.0005040031],"domain_scores_gemma":[0.9827617,0.01414304,0.0008667924,0.0006277718,0.0009427562,0.0006579566],"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":[0.001072691,0.0001542646,0.001051434,0.0002246652,0.00007365867,0.0001820863,0.0001452813,0.8973718,0.003394127,0.06815722,0.002521702,0.02565106],"study_design_scores_gemma":[0.0001000755,0.0002020192,0.0002147169,0.00001989021,0.00001507414,0.00008772715,0.00006139446,0.9772562,0.001562024,0.02015797,0.0003032546,0.00001957149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3724606,0.003018993,0.5887948,0.002952921,0.0002092851,0.0002259738,0.0003948453,0.0005696077,0.03137296],"genre_scores_gemma":[0.9700814,0.0007820104,0.02622577,0.000239807,0.00007184227,0.00008232352,0.0002034449,0.00006703453,0.002246384],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004828281,"threshold_uncertainty_score":0.02553469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02342508297852596,"score_gpt":0.2628776841207789,"score_spread":0.2394526011422529,"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."}}