{"id":"W2112798413","doi":"10.1109/sahcn.2006.288405","title":"GMR: Geographic Multicast Routing for Wireless Sensor Networks","year":2006,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multicast; Computer network; Computer science; Distance Vector Multicast Routing Protocol; Geographic routing; Protocol Independent Multicast; Xcast; Source-specific multicast; Unicast; Node (physics); Pragmatic General Multicast; Routing (electronic design automation); Distributed computing; Routing protocol; Static routing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007226414,0.0007517665,0.0006086424,0.0007562938,0.0004993918,0.000735867,0.001420172,0.0009519455,0.004185307],"category_scores_gemma":[0.001215391,0.0002579796,0.0005650686,0.0009534476,0.0004074892,0.001793414,0.001719152,0.0008270626,0.00162151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003929649,"about_ca_system_score_gemma":0.0004583874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008564048,"about_ca_topic_score_gemma":0.001007801,"domain_scores_codex":[0.9993068,0.0002233978,0.00003854537,0.00007646372,0.0002823924,0.00007229911],"domain_scores_gemma":[0.999778,0.00005123731,0.00003302402,0.00007004472,0.00004402281,0.00002372874],"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":[0.0002637677,0.00008554027,0.0006315449,0.001004455,0.0001263358,0.0005905826,0.0002341521,0.06268114,0.02805242,0.1128436,0.05199375,0.7414927],"study_design_scores_gemma":[0.0001616558,0.0004698347,0.0008234499,0.0001761228,0.0001082517,0.001299239,0.0001130285,0.4462815,0.02794833,0.08779018,0.4347251,0.0001032312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007590492,0.004772115,0.9688466,0.00115694,0.0005733558,0.0002634351,0.0005195987,0.00767669,0.008600781],"genre_scores_gemma":[0.1443316,0.004785153,0.8355028,0.0008972868,0.000565204,0.0005091491,0.002253119,0.0005842377,0.0105713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004185307,"threshold_uncertainty_score":0.01400131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008214282935130164,"score_gpt":0.213036950470551,"score_spread":0.2048226675354208,"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."}}