{"id":"W2061379834","doi":"10.1109/cce.2012.6315875","title":"Multisensor data fusion for water quality monitoring using wireless sensor networks","year":2012,"lang":"en","type":"article","venue":"","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Fusion center; Wireless sensor network; Sensor fusion; Fusion; Flexibility (engineering); A priori and a posteriori; Wireless; Focus (optics); Set (abstract data type)","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":[0.000968052,0.0006718209,0.0007080656,0.0006168399,0.0004070646,0.0006116489,0.0007775201,0.0007601691,0.0006682512],"category_scores_gemma":[0.002430897,0.0002212453,0.0004576085,0.001008782,0.0003968505,0.001347025,0.0008835058,0.0006385639,0.0001473754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005373926,"about_ca_system_score_gemma":0.0004097127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001262026,"about_ca_topic_score_gemma":0.001643018,"domain_scores_codex":[0.9993892,0.0002379951,0.00003456129,0.0001125557,0.000192622,0.00003310604],"domain_scores_gemma":[0.9993833,0.0003770473,0.00008411003,0.00006565313,0.00007671178,0.00001305812],"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":[0.0002561586,0.00009940702,0.001559889,0.0003908867,0.0001177061,0.0001122983,0.000116748,0.7065153,0.0288247,0.01016262,0.0008826906,0.2509616],"study_design_scores_gemma":[0.000007814411,0.00005519736,0.0004976792,0.000008931685,0.00001722026,0.00002908233,0.0000245404,0.9869177,0.005895551,0.005458552,0.001077191,0.00001048782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01738934,0.001437916,0.9801001,0.0001929398,0.00005145168,0.0000245716,0.00002987204,0.0001545457,0.0006193507],"genre_scores_gemma":[0.760763,0.001801767,0.2360511,0.0001180065,0.0000982345,0.00008973599,0.0001032182,0.0000259798,0.0009490116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001262026,"threshold_uncertainty_score":0.005119622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1345040349582941,"score_gpt":0.3520284985910653,"score_spread":0.2175244636327713,"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."}}