{"id":"W42863969","doi":"10.1201/9781420040401.ch15","title":"Adaptive Routing in Ad Hoc Networks","year":2002,"lang":"en","type":"book-chapter","venue":"˜The œelectrical engineering handbook/Electrical engineering handbook series/Electrical engineering handbook","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Adaptive quality of service multi-hop routing; Computer science; Computer network; Wireless ad hoc network; Mobile ad hoc network; Routing (electronic design automation); Optimized Link State Routing Protocol; Routing protocol; Telecommunications; Network packet; Wireless","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":[0.00112498,0.001335409,0.001053598,0.001422698,0.0007655537,0.002611047,0.001778756,0.002355939,0.004919503],"category_scores_gemma":[0.00360988,0.0005632484,0.0004592711,0.003083631,0.001515452,0.003082032,0.001563156,0.002422614,0.003580289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008568472,"about_ca_system_score_gemma":0.0009756716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009445102,"about_ca_topic_score_gemma":0.0006614963,"domain_scores_codex":[0.998102,0.000596093,0.0001360094,0.0002161662,0.0008763512,0.00007345602],"domain_scores_gemma":[0.9986647,0.0006623211,0.0001078326,0.0001722982,0.0003300665,0.0000627106],"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":[0.0000483635,0.00007600785,0.0006305844,0.001607429,0.00008981325,0.0005439955,0.0003607946,0.04686138,0.003173838,0.2880715,0.05582131,0.602715],"study_design_scores_gemma":[0.00005751133,0.0001539102,0.0005862878,0.0006419962,0.00006333194,0.001193436,0.0001853253,0.099821,0.001115676,0.296688,0.5994045,0.00008898012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004058835,0.1239456,0.7779453,0.005938734,0.006906359,0.0007670403,0.0003864339,0.003329894,0.07672174],"genre_scores_gemma":[0.1983434,0.2033129,0.5110464,0.003976125,0.009525792,0.002516436,0.001992955,0.0006778791,0.06860813],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004919503,"threshold_uncertainty_score":0.01645738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007558845454273174,"score_gpt":0.1709345007159196,"score_spread":0.1633756552616464,"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."}}