{"id":"W4245329270","doi":"10.1504/ijsnet.2019.103040","title":"Fixed node assisted collection tree protocol for mobile wireless sensor networks","year":2019,"lang":"en","type":"article","venue":"International Journal of Sensor Networks","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Computer network; Network packet; Wireless sensor network; Mobile ad hoc network; Node (physics); Distributed computing; Routing protocol; Overhead (engineering); Mobile computing; Tree (set theory); Mobile wireless sensor network; Wireless network; Key distribution in wireless sensor networks; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009538206,0.0005548098,0.0005943055,0.0007166223,0.0007992637,0.0009034731,0.001664553,0.0009698198,0.003081645],"category_scores_gemma":[0.002244916,0.0002331261,0.0004478116,0.001517261,0.00061385,0.001531462,0.00117109,0.001643899,0.001298551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006949642,"about_ca_system_score_gemma":0.001270495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00101267,"about_ca_topic_score_gemma":0.001750149,"domain_scores_codex":[0.9992562,0.0002199836,0.00006388684,0.00007230489,0.0003378784,0.00004983401],"domain_scores_gemma":[0.9993016,0.0002019877,0.0001120584,0.0001351915,0.0002056951,0.00004342595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003492346,0.0001565036,0.0008188111,0.002091307,0.0001937108,0.00120293,0.000568495,0.04534034,0.06656648,0.2640098,0.08616037,0.5325419],"study_design_scores_gemma":[0.0001794651,0.0008787496,0.0011078,0.0004356199,0.00014771,0.003673015,0.0002405935,0.2357465,0.02150344,0.08676828,0.6490834,0.000235527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005008813,0.009857865,0.9641327,0.00141156,0.001232462,0.0008449705,0.0004171661,0.001635358,0.0154591],"genre_scores_gemma":[0.2491287,0.01562535,0.6958048,0.001962063,0.000904056,0.004017254,0.002295496,0.0004149842,0.02984733],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003081645,"threshold_uncertainty_score":0.01030916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501897044647539,"score_gpt":0.2815774823300051,"score_spread":0.2665585118835297,"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."}}