{"id":"W2096124156","doi":"10.1109/glocom.2010.5683928","title":"Localization of Wireless Sensors via Nuclear Norm for Rank Minimization","year":2010,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Minification; Computer science; Wireless; Rank (graph theory); Wireless sensor network; Norm (philosophy); Mathematical optimization; Mathematics; Computer network; Telecommunications; Combinatorics; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004981812,0.00008951231,0.0001197313,0.0001016379,0.00004355092,0.00001150917,0.00009434285,0.0001615834,0.0001327008],"category_scores_gemma":[0.00004107907,0.00008576971,0.00004073074,0.0001838378,0.00004629843,0.0000898869,0.00001087027,0.00006457027,0.00001129859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001066845,"about_ca_system_score_gemma":0.000004744046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007496773,"about_ca_topic_score_gemma":0.00002109995,"domain_scores_codex":[0.9995021,0.000003492283,0.0002039583,0.00008973647,0.00007892987,0.000121766],"domain_scores_gemma":[0.9996539,0.0000277867,0.00003177623,0.0001559668,0.0001097602,0.00002074934],"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":[0.00009362362,0.0001295782,0.002458743,0.0009279725,0.000129334,0.000001529237,0.001507497,0.530718,0.2141318,0.1340415,0.01541259,0.1004478],"study_design_scores_gemma":[0.0002904797,0.00001814227,0.00005499394,0.000005075618,0.000009377816,0.000001359312,0.0001012115,0.8061126,0.1857031,0.0004056201,0.007191264,0.0001068167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1244272,0.000006439042,0.8716407,0.00003822752,0.0003809774,0.0002265112,0.000007670486,0.0007677376,0.002504545],"genre_scores_gemma":[0.9946009,0.00001765058,0.00516891,0.0000274896,0.00003431813,0.000008940766,0.00002818362,0.00003449644,0.00007912017],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8701737,"threshold_uncertainty_score":0.3497587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004859284037641126,"score_gpt":0.1946291923638244,"score_spread":0.1897699083261833,"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."}}