{"id":"W2154744516","doi":"10.1109/ccece.2006.277328","title":"Hybrid Position-Based 3D Routing Algorithms with Partial Flooding","year":2006,"lang":"en","type":"article","venue":"","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Destination-Sequenced Distance Vector routing; Computer science; Link-state routing protocol; Static routing; Dynamic Source Routing; Flooding (psychology); Equal-cost multi-path routing; Algorithm; Wireless Routing Protocol; Zone Routing Protocol; Routing table; Multipath routing; Policy-based routing; Computer network; Geographic routing; Distributed computing; Routing (electronic design automation); Routing protocol","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001862279,0.0001433728,0.0001274255,0.00004676983,0.0001819959,0.0002497926,0.0004159088,0.00002977674,0.00004866598],"category_scores_gemma":[0.0000037844,0.0001177925,0.00004035825,0.0002317151,0.00003471188,0.0003321261,0.00007913771,0.0001155161,0.0000517564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000495374,"about_ca_system_score_gemma":0.00007110219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002362527,"about_ca_topic_score_gemma":0.00002818925,"domain_scores_codex":[0.9986702,0.00004175125,0.0002032617,0.0003973245,0.0002953809,0.0003921203],"domain_scores_gemma":[0.9992883,0.00008975504,0.00007270411,0.0004212648,0.00005775568,0.00007019928],"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":[0.00003832468,0.0004581873,0.00828477,0.00002373009,0.00005549539,0.0006677803,0.0001195238,0.6435546,0.001422433,0.2419514,0.007603245,0.0958205],"study_design_scores_gemma":[0.0004150066,0.00007584028,0.000354492,0.00002463527,0.000006071234,0.00003207024,0.000002178989,0.9841931,0.01382503,0.0003838252,0.0004885361,0.0001991995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01586173,0.00001788018,0.9710178,0.0003918835,0.0001729643,0.0001445502,9.43655e-7,0.0004087218,0.01198347],"genre_scores_gemma":[0.7886657,1.723024e-7,0.2104788,0.0003694285,0.0002934857,0.00001957803,0.000007381416,0.00001033078,0.0001551013],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.772804,"threshold_uncertainty_score":0.4803439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006891157685412839,"score_gpt":0.2056417677706994,"score_spread":0.1987506100852866,"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."}}