{"id":"W2800822458","doi":"10.3390/jsan7020020","title":"Optimization of Wireless Sensor Networks Deployment Based on Probabilistic Sensing Models in a Complex Environment","year":2018,"lang":"en","type":"article","venue":"Journal of Sensor and Actuator Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Wireless sensor network; Software deployment; Probabilistic logic; Optimization problem; Global optimization; Evolutionary algorithm; Convergence (economics); Genetic algorithm; Process (computing); Algorithm; Mathematical optimization; Distributed computing; Machine learning; Artificial intelligence; Computer network","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":[0.0009594352,0.001161657,0.0008315318,0.0004679655,0.0003361718,0.0008406967,0.0008071793,0.0006951391,0.0004768321],"category_scores_gemma":[0.001837111,0.0004814512,0.000760982,0.0008814634,0.0007153068,0.001166583,0.0008566827,0.0006253839,0.0001053954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008031306,"about_ca_system_score_gemma":0.0009057067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004704872,"about_ca_topic_score_gemma":0.002987529,"domain_scores_codex":[0.9992881,0.0002694197,0.00002974974,0.000169146,0.0001753276,0.00006814356],"domain_scores_gemma":[0.999384,0.0003641332,0.0001157447,0.00003727109,0.00007909178,0.00001966005],"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":[0.000007396725,0.000004652425,0.000148938,0.00001694536,0.000007338695,0.00001188472,0.00000892554,0.995599,0.0004164328,0.00111747,0.00005660236,0.002604358],"study_design_scores_gemma":[0.000001465304,0.0000103335,0.00008564715,0.000002101663,0.00000278243,0.000005879337,0.000005625007,0.99876,0.0001574921,0.0008799629,0.00008695401,0.000001806653],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04384002,0.0005997594,0.9528377,0.000183077,0.00002013159,0.00004060209,0.000049963,0.0001741253,0.002254618],"genre_scores_gemma":[0.8806643,0.001458853,0.1156941,0.00006416899,0.00002611523,0.0001823883,0.000132406,0.00006802553,0.001709508],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004704872,"threshold_uncertainty_score":0.009354949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01813729997012134,"score_gpt":0.2192117300961279,"score_spread":0.2010744301260066,"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."}}