{"id":"W2786827427","doi":"10.5539/ijsp.v7n2p39","title":"WSN Node Positioning and Mathematics Modeling Based on Genetic Method","year":2018,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Chongqing Municipal Education Commission; China Scholarship Council; Ministry of Education of the People's Republic of China; National Office for Philosophy and Social Sciences; National Natural Science Foundation of China","keywords":"Wireless sensor network; Node (physics); Computer science; Genetic algorithm; Trajectory; Sampling (signal processing); Algorithm; Sample (material); Real-time computing; Computer network; Machine learning; Computer vision; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002900198,0.0005406523,0.0005171938,0.0008020909,0.0003839764,0.0006927348,0.0009728377,0.0006656097,0.001009085],"category_scores_gemma":[0.0007212263,0.0002332748,0.0007763159,0.001122779,0.000526993,0.001054195,0.0004581899,0.0005602668,0.0003589518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006692928,"about_ca_system_score_gemma":0.000674942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009516519,"about_ca_topic_score_gemma":0.003370751,"domain_scores_codex":[0.9997292,0.0000591749,0.00001384506,0.0000667038,0.0001109459,0.00002009655],"domain_scores_gemma":[0.9998461,0.00006230819,0.00002440228,0.00001220111,0.00004803457,0.000006913136],"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":[0.00001617963,0.0000143113,0.0009546503,0.00006954477,0.00002140348,0.0001074389,0.00008622519,0.9446976,0.003639138,0.02513948,0.0005170826,0.02473699],"study_design_scores_gemma":[0.00000277025,0.00001379562,0.0002522101,0.000005296232,0.000005847575,0.00004229983,0.000009950477,0.9927375,0.0003943155,0.005446121,0.001081046,0.000008739024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01113813,0.0006152497,0.9836029,0.0001952985,0.00006126842,0.00002897385,0.00005357556,0.0001804693,0.004124094],"genre_scores_gemma":[0.7493826,0.004787863,0.2318063,0.0001292062,0.0001696988,0.000291688,0.0003027249,0.000104731,0.01302519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009516519,"threshold_uncertainty_score":0.01892221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401117164497161,"score_gpt":0.2715601056457642,"score_spread":0.2575489340007925,"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."}}