{"id":"W2131633956","doi":"10.1109/mahss.2005.1542826","title":"Distortion sum-rate performance of successive coding strategy in gaussian wireless sensor networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Wireless sensor network; Rate distortion; Computer science; Gaussian; Distortion (music); Coding (social sciences); Rate–distortion theory; Distributed source coding; Decoding methods; Algorithm; Source code; Mathematical optimization; Mathematics; Channel code; Telecommunications; Statistics; Computer network; Bandwidth (computing); Data compression","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":[0.0001915009,0.000125058,0.0001880971,0.000120156,0.00003093056,0.00001938558,0.0002211854,0.0001011893,0.00005045438],"category_scores_gemma":[0.000005344314,0.0001300433,0.00002914276,0.0002368397,0.00004162065,0.00033611,0.00003527956,0.0002339208,0.000005657594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001183167,"about_ca_system_score_gemma":0.000009783354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006451346,"about_ca_topic_score_gemma":0.0004935936,"domain_scores_codex":[0.9991971,0.00004205354,0.0003672454,0.0001081469,0.00008925368,0.0001961945],"domain_scores_gemma":[0.9994758,0.00005758774,0.00006778646,0.0003191599,0.00004076624,0.00003884313],"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":[0.00003110253,0.00009556425,0.01796493,0.0002049987,0.00002792008,0.000003020631,0.0007272505,0.9035671,0.01529586,0.006988308,0.0003614734,0.05473246],"study_design_scores_gemma":[0.0001512897,0.00001879659,0.01362646,0.00009890307,0.000003183829,0.000001232122,0.00009084371,0.9364955,0.04916539,0.000008969097,0.0001748881,0.0001645011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683989,0.0001896994,0.02360234,0.00005847899,0.00002994708,0.0001412254,0.000002254703,0.0003644225,0.007212739],"genre_scores_gemma":[0.9982184,0.0008054511,0.0007981074,0.00001524258,0.00003605691,0.00002230879,0.00001494549,0.0000239052,0.00006558719],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05456796,"threshold_uncertainty_score":0.5303012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215083338712965,"score_gpt":0.2383573539823131,"score_spread":0.2262065205951835,"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."}}