{"id":"W2029490954","doi":"10.1109/smc.2014.6974269","title":"Multisensors realtime data fusion optimization for IOT systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Water Quality Monitoring Technologies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Terry Fox Research Institute; National Science Council","keywords":"Real-time computing; Computer science; Microcontroller; Battery (electricity); Sensor fusion; Wireless; SIGNAL (programming language); Embedded system; Wireless sensor network; Power (physics); Computer network; Artificial intelligence; Telecommunications","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000483508,0.00007863811,0.00009162157,0.00002008191,0.00009393296,0.00003376951,0.0005289392,0.00007553594,0.00009456114],"category_scores_gemma":[0.0002569431,0.00006354858,0.00001201851,0.00007318169,0.00006291173,0.00008500524,0.0005565183,0.00003770395,0.0001581473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006119187,"about_ca_system_score_gemma":0.000001757759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009259395,"about_ca_topic_score_gemma":0.00001784774,"domain_scores_codex":[0.9991608,0.00004093353,0.000157107,0.0003170522,0.0001538297,0.0001703398],"domain_scores_gemma":[0.9989892,0.00008675929,0.00005486128,0.0008308033,0.000005666529,0.00003272014],"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":[0.00002805892,0.0001006601,0.01390395,0.00006696991,0.0000114956,6.781159e-7,0.0001464533,0.9026065,0.01093502,0.001452029,0.04263096,0.02811716],"study_design_scores_gemma":[0.0001789322,0.00004328293,0.0009941286,0.000009541655,0.000005430108,0.000001085507,0.00005940831,0.9801539,0.003350656,0.0001500436,0.01493808,0.0001155784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4271706,0.00001465915,0.5634994,0.00195225,0.0009191859,0.001143767,0.00006236319,0.001428899,0.003808891],"genre_scores_gemma":[0.7004784,0.00000501004,0.2976323,0.0000294689,0.0000789429,0.00002556346,0.00006847007,0.00001567419,0.001666103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2733078,"threshold_uncertainty_score":0.2591436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0706232028161838,"score_gpt":0.2924329670492477,"score_spread":0.2218097642330639,"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."}}