{"id":"W2130412147","doi":"10.1002/wcm.2333","title":"Improving routing in networks of Unmanned Aerial Vehicles: Reactive‐Greedy‐Reactive","year":2012,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Zone Routing Protocol; Wireless Routing Protocol; Computer network; Link-state routing protocol; Optimized Link State Routing Protocol; Dynamic Source Routing; Routing protocol; Distributed computing; Destination-Sequenced Distance Vector routing; Routing (electronic design automation)","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":[0.001039277,0.0006924826,0.0002757953,0.0004874671,0.000400655,0.0005149419,0.001047431,0.0004814131,0.001174856],"category_scores_gemma":[0.001794894,0.0002107512,0.0002705534,0.0004788762,0.0005399869,0.0009927109,0.001112378,0.000538569,0.0002729388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003720006,"about_ca_system_score_gemma":0.0003805134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00137212,"about_ca_topic_score_gemma":0.002303105,"domain_scores_codex":[0.9994532,0.0001860532,0.00002601035,0.00007334797,0.000199371,0.00006206591],"domain_scores_gemma":[0.9992253,0.000302937,0.0001430174,0.0001335682,0.0001481549,0.00004702949],"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":[0.0002212271,0.0001215411,0.001964433,0.00023621,0.0001588848,0.0003010688,0.0001976532,0.7062702,0.07605229,0.03436595,0.005637914,0.1744727],"study_design_scores_gemma":[0.00003499028,0.0002077455,0.000392962,0.00001678746,0.00004633754,0.0001768175,0.00007028667,0.9678227,0.01646918,0.006813061,0.007922751,0.00002649424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1151263,0.001657634,0.8706697,0.000764037,0.0003262174,0.0001532822,0.00005994345,0.00134504,0.009897776],"genre_scores_gemma":[0.7943881,0.000781948,0.2005492,0.0003314382,0.00007708751,0.00007624357,0.00009953515,0.00008670017,0.003609771],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00137212,"threshold_uncertainty_score":0.005496323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01628271164653725,"score_gpt":0.2591445560905831,"score_spread":0.2428618444440458,"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."}}