{"id":"W2192655756","doi":"10.1002/wcm.2653","title":"Three dimensional compressed sensing for wireless networks‐based multiple node localization in multi‐floor buildings","year":2015,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Node (physics); Compressed sensing; Wireless; Position (finance); Transmission (telecommunications); Wireless network; Fading; Shadow mapping; Real-time computing; Radio propagation; Noise (video); Path loss; Algorithm; Telecommunications; Artificial intelligence; Acoustics","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":[0.0003567378,0.0003203203,0.0002997121,0.0004168687,0.0001777268,0.0003628783,0.0003479061,0.0003412397,0.0005280383],"category_scores_gemma":[0.001231966,0.0001412741,0.0002374584,0.0004202035,0.0004247291,0.0005249575,0.0005895745,0.0003250402,0.00009392164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002980977,"about_ca_system_score_gemma":0.0003383339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00221384,"about_ca_topic_score_gemma":0.001517711,"domain_scores_codex":[0.9997508,0.00008607365,0.000009992582,0.00003303097,0.0001033992,0.00001661153],"domain_scores_gemma":[0.9994405,0.0003276464,0.00007316295,0.00004594249,0.00009229394,0.0000203663],"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":[0.0002191498,0.00005463029,0.001288451,0.0001559682,0.00004003242,0.0002384167,0.0001751973,0.8073397,0.04170566,0.008500873,0.001044495,0.1392374],"study_design_scores_gemma":[0.000003657687,0.00002231842,0.0002252983,0.000003719003,0.000002747964,0.00002135624,0.0000122816,0.9963819,0.002261779,0.0008440592,0.0002163626,0.000004435859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1080553,0.0003770474,0.8895287,0.0002710593,0.00006784229,0.00002781848,0.00004334389,0.0003040338,0.00132488],"genre_scores_gemma":[0.9041288,0.0002577062,0.09485383,0.00005832084,0.00002855685,0.0000371823,0.00005855524,0.0000159856,0.0005611408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00221384,"threshold_uncertainty_score":0.004401922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03622053266496306,"score_gpt":0.2649202017488933,"score_spread":0.2286996690839302,"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."}}