{"id":"W865478343","doi":"","title":"Models For Locating RFID Nodes","year":2006,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wireless sensor network; Computer science; Scalability; Distributed computing; Flexibility (engineering); Triangulation; Key distribution in wireless sensor networks; Range (aeronautics); Wireless; Wireless ad hoc network; Real-time computing; Field (mathematics); Computer network; Wireless network; Engineering; Telecommunications; Geography","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":[0.001217137,0.001236655,0.001062609,0.001391167,0.0007268134,0.002305541,0.004342204,0.003757987,0.007368019],"category_scores_gemma":[0.005470873,0.0008148503,0.001373083,0.002259651,0.001260845,0.003526971,0.00164088,0.001351741,0.003950676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229918,"about_ca_system_score_gemma":0.0006378262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005567445,"about_ca_topic_score_gemma":0.003194471,"domain_scores_codex":[0.9991367,0.0002694355,0.00005382314,0.0001990317,0.0002257448,0.000115262],"domain_scores_gemma":[0.9982892,0.0008943418,0.0002439857,0.0002376445,0.0002809161,0.00005390293],"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":[0.00003613541,0.00001538013,0.0004281088,0.00007052551,0.00001822059,0.0001559361,0.0001210691,0.8321896,0.0004841527,0.1550034,0.001986096,0.009491471],"study_design_scores_gemma":[0.00001245665,0.00002225021,0.0001026073,0.00001638892,0.00001254961,0.00009489003,0.00004224318,0.946993,0.0001738401,0.04760222,0.004909936,0.00001769167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007750788,0.001030002,0.9707339,0.0007477597,0.0001879705,0.00005872903,0.0004835378,0.0003927784,0.01861463],"genre_scores_gemma":[0.6930172,0.006164171,0.2047539,0.0005777426,0.0005728776,0.001030304,0.001903944,0.000413392,0.09156656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007368019,"threshold_uncertainty_score":0.02464849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009047023237069901,"score_gpt":0.1886198079561913,"score_spread":0.1795727847191214,"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."}}