{"id":"W2054562163","doi":"10.1109/smc.2014.6974030","title":"Source-reliability-adaptive distributed information fusion","year":2014,"lang":"en","type":"article","venue":"","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Particle filter; Wireless sensor network; Robustness (evolution); Soft sensor; Sensor fusion; Scalability; Distributed computing; Reliability (semiconductor); Real-time computing; Sensor node; Node (physics); Kalman filter; Process (computing); Key distribution in wireless sensor networks; Engineering; Artificial intelligence; Wireless; Wireless network","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":[0.001238211,0.0008499066,0.001178489,0.0008243875,0.0004484769,0.0008857842,0.001694506,0.001014315,0.0007235111],"category_scores_gemma":[0.004342926,0.0004571392,0.0008250935,0.0009785705,0.0006084666,0.001503838,0.001863155,0.00123851,0.0003073429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007190035,"about_ca_system_score_gemma":0.001058198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002474633,"about_ca_topic_score_gemma":0.00217702,"domain_scores_codex":[0.9988514,0.000245239,0.00005657526,0.0002784755,0.0005026711,0.00006559303],"domain_scores_gemma":[0.9986155,0.0005432573,0.0001651838,0.0001891771,0.0004477229,0.00003907812],"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":[0.0001320973,0.00006083571,0.0006180202,0.0001323606,0.0000892437,0.0001242588,0.0001620521,0.7929285,0.01158613,0.0223154,0.001724318,0.1701269],"study_design_scores_gemma":[0.000007011943,0.00001611051,0.00009542579,0.000003021298,0.000005923944,0.00001824707,0.000004572372,0.9944295,0.001227434,0.003668723,0.0005164202,0.000007594339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001550472,0.00005432016,0.997881,0.00004255379,0.00001895928,0.000012015,0.00000933216,0.00009894507,0.0003324478],"genre_scores_gemma":[0.5869997,0.0003979743,0.4084382,0.0001604929,0.0001318603,0.0002300332,0.0002252963,0.0001013512,0.003315251],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002474633,"threshold_uncertainty_score":0.006548345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006865835337522193,"score_gpt":0.1975144924842166,"score_spread":0.1906486571466944,"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."}}