{"id":"W2145979466","doi":"10.1109/tsmc.2014.2356437","title":"The Smart-Condo: Optimizing Sensor Placement for Indoor Localization","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Systems","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Software deployment; Computer science; Cardinality (data modeling); Constraint (computer-aided design); Space (punctuation); Optimization problem; Artificial intelligence; Human–computer interaction; Simple (philosophy); Real-time computing; Computer vision; Distributed computing; Data mining; Algorithm; Mathematics","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":[0.0006522257,0.001219306,0.0007553617,0.0005672162,0.0003181051,0.0004991512,0.0008733959,0.0008336294,0.001720352],"category_scores_gemma":[0.002779386,0.0004646661,0.0004192755,0.0007002244,0.0006514088,0.0006958953,0.0008182731,0.000483257,0.0004332528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007291874,"about_ca_system_score_gemma":0.001168119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004897136,"about_ca_topic_score_gemma":0.007234342,"domain_scores_codex":[0.9995725,0.0001592815,0.00001395633,0.00008848442,0.0001071321,0.00005875846],"domain_scores_gemma":[0.9993179,0.0003656101,0.0001111126,0.00007660528,0.00008118137,0.00004767894],"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":[0.00004213887,0.00002007441,0.0005047783,0.00003748935,0.00001003917,0.0000272835,0.00001670135,0.9803388,0.00162098,0.001811,0.0008599942,0.0147107],"study_design_scores_gemma":[0.000007615084,0.00003223946,0.0001352495,0.000003237735,0.000002753444,0.00001832036,0.000009609419,0.9978109,0.0005022384,0.00110618,0.0003682571,0.000003384547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02380667,0.0002018703,0.9731611,0.0001571454,0.00002859967,0.00006241948,0.0001340141,0.0005955571,0.001852699],"genre_scores_gemma":[0.5791899,0.000207727,0.417484,0.00009371727,0.00003352256,0.0001891271,0.0002743416,0.0001927867,0.002334953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004897136,"threshold_uncertainty_score":0.009737313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026958772464871,"score_gpt":0.2025035732971197,"score_spread":0.192233985572471,"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."}}