{"id":"W2085470892","doi":"10.3390/jsan1010036","title":"Localization in Wireless Sensor Networks and Anchor Placement","year":2012,"lang":"en","type":"article","venue":"Journal of Sensor and Actuator Networks","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Wireless sensor network; Computer science; Node (physics); Global Positioning System; Protocol (science); Set (abstract data type); Class (philosophy); Computer network; Position (finance); Curvilinear coordinates; Distributed computing; Artificial intelligence; Mathematics; Engineering; Telecommunications","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":[0.001194668,0.001126804,0.0007888734,0.001079918,0.0006160323,0.001661679,0.001043214,0.002010767,0.002817149],"category_scores_gemma":[0.004367557,0.0003979423,0.0004908347,0.002966108,0.002402899,0.002767688,0.001388839,0.001546396,0.001298793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008388874,"about_ca_system_score_gemma":0.0007163993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001210998,"about_ca_topic_score_gemma":0.0008969372,"domain_scores_codex":[0.9981352,0.0007143421,0.0000951492,0.0002552386,0.0007252151,0.00007477162],"domain_scores_gemma":[0.9986923,0.000740242,0.0001951857,0.0001364056,0.0002024946,0.00003336753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006472786,0.00005316068,0.001049419,0.001193513,0.00006603245,0.0004694275,0.0002580727,0.2760157,0.004950656,0.4220342,0.01436647,0.2794785],"study_design_scores_gemma":[0.00003761337,0.0003280693,0.001274892,0.0005378366,0.00006025935,0.001312835,0.0003085286,0.3357035,0.003761881,0.4869998,0.1695711,0.0001036348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004679185,0.04457089,0.9187535,0.002590552,0.001482479,0.0001081333,0.0001016492,0.000447542,0.02726617],"genre_scores_gemma":[0.3838694,0.1430584,0.438631,0.001650049,0.004881508,0.0006622659,0.0005106418,0.0002751678,0.0264616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002817149,"threshold_uncertainty_score":0.009424329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006988768717321359,"score_gpt":0.2051615135592725,"score_spread":0.1981727448419511,"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."}}