{"id":"W2108773413","doi":"10.1109/iwqos.2007.376548","title":"Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors","year":2007,"lang":"en","type":"article","venue":"International Workshop on Quality of Service","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Scheduling (production processes); Probabilistic logic; Wireless sensor network; Distributed computing; Overhead (engineering); Real-time computing; Exploit; Computer network; Engineering","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":[0.001093653,0.0001554506,0.000288845,0.00009028752,0.00005314975,0.00004178929,0.0006221014,0.0000703444,0.00002325848],"category_scores_gemma":[0.000195109,0.0001592956,0.00006370906,0.0003991453,0.00005602931,0.0001679116,0.0002306794,0.0001765816,0.000002481987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006476107,"about_ca_system_score_gemma":0.00003593959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002611838,"about_ca_topic_score_gemma":0.0001003115,"domain_scores_codex":[0.9979842,0.0001175641,0.0006902995,0.0003502082,0.0006009915,0.000256777],"domain_scores_gemma":[0.9962527,0.00240717,0.0004461017,0.0004077299,0.0004068963,0.00007940219],"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":[0.0001322741,0.0001790213,0.0007363404,0.00009849103,0.00005576188,0.0000103577,0.0006280617,0.9574959,0.00056194,0.03322475,0.0000780762,0.006799075],"study_design_scores_gemma":[0.0007975937,0.0001539421,0.004996547,0.0007126607,0.00001593291,0.00002258704,0.000188072,0.981913,0.003830832,0.006392753,0.0005973155,0.0003787859],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7459149,0.00005502448,0.2521253,0.0006284239,0.0004079181,0.0001424496,0.000007358591,0.00003368271,0.0006850208],"genre_scores_gemma":[0.9828457,0.00001699966,0.01565097,0.00130733,0.0001008981,0.000003106338,0.000007391272,0.00001061581,0.00005703005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2369308,"threshold_uncertainty_score":0.6495885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383180869374273,"score_gpt":0.3232705276578743,"score_spread":0.2894387189641316,"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."}}