{"id":"W2786312404","doi":"10.1109/dcoss.2017.22","title":"Multi-sensor and Information-Based Event Triggered Distributed Estimation","year":2017,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Wireless sensor network; Computer science; Filter (signal processing); Sensor fusion; State (computer science); Distributed computing; Information fusion; Soft sensor; Information filtering system; Topology (electrical circuits); Real-time computing; Computer network; Engineering; Artificial intelligence; Algorithm","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0001623464,0.0001145584,0.0001189393,0.00006295183,0.0005705945,0.001073896,0.0003930033,0.00006441218,0.000017849],"category_scores_gemma":[0.0001910664,0.0000985088,0.00004419909,0.0000948965,0.00005219604,0.001945122,0.0001001807,0.00007990847,0.0000618807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003045864,"about_ca_system_score_gemma":0.00003572475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005814945,"about_ca_topic_score_gemma":0.000006934625,"domain_scores_codex":[0.9991954,0.00002262933,0.0002398074,0.0001736183,0.0001853109,0.0001832363],"domain_scores_gemma":[0.9988773,0.00005183923,0.0002030181,0.0006136823,0.0001306614,0.0001234494],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005290209,0.0002527243,0.001295346,0.00005248501,0.00006006606,0.00001758506,0.0001647914,0.06670565,0.0001448852,0.02036069,0.005998699,0.9048942],"study_design_scores_gemma":[0.0009545611,0.00003166624,0.01911687,0.00000881888,0.000003791698,0.000003967671,0.000008963054,0.9736142,0.0004926265,0.000190604,0.00543934,0.0001345655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002252385,0.000009548885,0.9950239,0.00163021,0.0003127046,0.0001621666,0.00003861305,0.0002155151,0.0003549733],"genre_scores_gemma":[0.8232198,0.000006088386,0.1762332,0.0003398354,0.00002194081,0.00001294268,0.00006256264,0.000003364129,0.0001002348],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9069086,"threshold_uncertainty_score":0.9999631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01421511303416499,"score_gpt":0.2573890810649193,"score_spread":0.2431739680307543,"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."}}