{"id":"W2127371329","doi":"10.1109/aina.2007.144","title":"Uniformity and Efficiency of a Wireless Sensor Network's Coverage","year":2007,"lang":"en","type":"article","venue":"Proceedings","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Wireless sensor network; Computer science; Key distribution in wireless sensor networks; Process (computing); Mobile wireless sensor network; Computer network; Wireless network; Wireless; Real-time computing; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009110486,0.0001879088,0.0002592732,0.000123658,0.0001440619,0.00009067782,0.0005517138,0.0001163673,0.000002645225],"category_scores_gemma":[0.00004095077,0.0001761862,0.00005298481,0.0009116959,0.0001357385,0.0003521067,0.0003200863,0.0001937042,0.000003641403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004563948,"about_ca_system_score_gemma":0.00002728874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000262044,"about_ca_topic_score_gemma":0.000005720719,"domain_scores_codex":[0.9982159,0.000007313645,0.0003661266,0.0004423549,0.000380241,0.0005881067],"domain_scores_gemma":[0.9990705,0.0001300673,0.0002240007,0.0001935851,0.0002243256,0.0001574758],"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":[0.0001158373,0.0004159141,0.09138377,0.0003183302,0.00006240969,0.00005362117,0.003871924,0.009139654,0.0145039,0.7697693,0.001028943,0.1093365],"study_design_scores_gemma":[0.002511591,0.000769908,0.05011581,0.0005003185,0.00005252305,0.0003910061,0.0005335892,0.866547,0.06431575,0.00477816,0.007746432,0.001737842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7816947,0.0001441799,0.2042345,0.0001012463,0.0001834016,0.0001277402,5.178397e-7,0.0001664106,0.01334734],"genre_scores_gemma":[0.9814641,0.00005382141,0.01803277,0.0001404531,0.0001285921,0.000002331333,5.418605e-7,0.00001443586,0.0001629746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8574074,"threshold_uncertainty_score":0.7184665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007069084689203071,"score_gpt":0.2123287148406274,"score_spread":0.2052596301514243,"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."}}