{"id":"W1987044550","doi":"10.1109/tvt.2014.2302232","title":"Distributed Deployment Algorithms for Efficient Coverage in a Network of Mobile Sensors With Nonidentical Sensing Capabilities","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; McGill University","funders":"National Institute of Standards and Technology","keywords":"Voronoi diagram; Software deployment; Wireless sensor network; Computer science; Position (finance); Real-time computing; Algorithm; Distributed computing; Computer network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003640571,0.0002574968,0.0004532827,0.0003133873,0.0001590468,0.00003378884,0.0004221658,0.0002847867,0.000001921559],"category_scores_gemma":[0.00001576331,0.0002365539,0.000125309,0.001206857,0.0002967268,0.00005835577,0.000009351424,0.0003661081,0.00000297313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001723773,"about_ca_system_score_gemma":0.0000496472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003738279,"about_ca_topic_score_gemma":0.0000983678,"domain_scores_codex":[0.9978836,0.0001177311,0.0004641059,0.000615734,0.0003151726,0.0006037092],"domain_scores_gemma":[0.9984493,0.0003838838,0.0001333447,0.0007874382,0.0001767337,0.00006929001],"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":[0.00003735625,0.000273497,0.00003365724,0.00002360148,0.00003681633,0.00001583046,0.00008102704,0.9792375,0.0006161284,0.003145571,0.000005230335,0.0164938],"study_design_scores_gemma":[0.001003568,0.0006526801,0.00003444526,0.0001287519,0.00002694032,0.00005369979,0.00006651582,0.9514519,0.04568985,0.0003647167,0.0002768289,0.000250122],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3983068,0.00002824979,0.6006811,0.0001841713,0.0001960681,0.0003720786,0.000007601209,0.0002178321,0.000006120357],"genre_scores_gemma":[0.9507235,0.00001138073,0.04905673,0.00003526771,0.00002126859,0.0001078711,0.000003464567,0.00002808493,0.00001244293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5524167,"threshold_uncertainty_score":0.9646389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006411325406490335,"score_gpt":0.2168613065763324,"score_spread":0.2104499811698421,"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."}}