{"id":"W2561875741","doi":"10.1002/wcm.2763","title":"Characterizing multi‐hop localization for Internet of things","year":2016,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; United Arab Emirates University","keywords":"Computer science; Hop (telecommunications); Implementation; Internet of Things; Distributed computing; Overhead (engineering); Gaussian; The Internet; Computer network; Reliability (semiconductor); Computer security; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001110388,0.0004457032,0.0003952534,0.0007136301,0.0004218724,0.0008609208,0.0005567003,0.001112729,0.000663586],"category_scores_gemma":[0.008227218,0.0002826818,0.0004266811,0.0007996046,0.000631029,0.001428578,0.0009246195,0.0004599484,0.0001355412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008529803,"about_ca_system_score_gemma":0.000468684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00186433,"about_ca_topic_score_gemma":0.001405547,"domain_scores_codex":[0.9991265,0.0003122015,0.00004412261,0.0001346707,0.0002686929,0.0001138327],"domain_scores_gemma":[0.9957761,0.002648364,0.0006725268,0.0004243904,0.0003943773,0.00008429484],"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":[0.00004465205,0.00003045581,0.004493477,0.00006622018,0.00003452826,0.0001488014,0.00006846312,0.9596558,0.004399032,0.02125945,0.0005265255,0.009272737],"study_design_scores_gemma":[0.0000030308,0.00003020912,0.0009991926,0.000008165947,0.000006593966,0.0001304405,0.00003687484,0.9871516,0.001175927,0.009921115,0.0005280045,0.000008751596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.209394,0.0005664827,0.784929,0.0007119732,0.00007856515,0.00008250717,0.0001314368,0.0002259364,0.003880075],"genre_scores_gemma":[0.9809812,0.0002605244,0.01801089,0.0000532794,0.00002129385,0.00004614695,0.00008449934,0.00001955861,0.0005226313],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00186433,"threshold_uncertainty_score":0.006188869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0188268427259609,"score_gpt":0.2523510637196933,"score_spread":0.2335242209937324,"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."}}