{"id":"W4206631577","doi":"10.5815/ijwmt.2021.03.05","title":"A Node Localization Algorithm based on WoaBp Optimization","year":2021,"lang":"en","type":"article","venue":"International Journal of Wireless and Microwave Technologies","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Artificial neural network; Real-time computing; Global Positioning System; Node (physics); Positioning technology; Positioning system; Wireless sensor network; Hybrid positioning system; Received signal strength indication; Algorithm; Artificial intelligence; Wireless; Engineering; Computer network; Telecommunications","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":[0.0005651569,0.0009683075,0.001187285,0.0008882991,0.000725153,0.0008656712,0.001200354,0.00116546,0.003547243],"category_scores_gemma":[0.001543355,0.0004638404,0.0006307397,0.001034003,0.000545014,0.0009848498,0.0009735433,0.0009227001,0.0008832794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007589987,"about_ca_system_score_gemma":0.001478125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01491445,"about_ca_topic_score_gemma":0.007867791,"domain_scores_codex":[0.9996502,0.0000684839,0.00001850776,0.00009713179,0.0001145383,0.00005116114],"domain_scores_gemma":[0.9997397,0.00008848539,0.00003005457,0.00001423722,0.0001134578,0.00001412919],"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":[0.00006090601,0.00002625573,0.0005761708,0.00006706586,0.00003032493,0.00005505513,0.00005610872,0.9007416,0.001926441,0.006031603,0.002063047,0.08836529],"study_design_scores_gemma":[0.000007349429,0.00001186792,0.00006476247,0.000004413101,0.000003771821,0.00001002007,0.00000615762,0.998376,0.0002640947,0.0007415497,0.0005067217,0.000003252887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006286893,0.0001875089,0.9899657,0.000146866,0.0000552938,0.00005216284,0.0000341699,0.0004070702,0.002864272],"genre_scores_gemma":[0.4249333,0.0005995956,0.5608621,0.0002331615,0.00009299352,0.0006414892,0.0003390956,0.0002120199,0.01208612],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01491445,"threshold_uncertainty_score":0.02965528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005516957282453784,"score_gpt":0.2088457894028356,"score_spread":0.2033288321203819,"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."}}