{"id":"W2091072140","doi":"10.1145/1362542.1362543","title":"Efficient geographic routing over lossy links in wireless sensor networks","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Sensor Networks","topic":"Mobile Ad Hoc Networks","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nokia (Canada)","funders":"National Science Foundation","keywords":"Computer science; Computer network; Lossy compression; Packet forwarding; Geographic routing; Wireless sensor network; Network packet; Virtual routing and forwarding; Routing (electronic design automation); Metric (unit); Routing table; Performance metric; Distributed computing; Routing protocol; Static routing","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":[0.001569847,0.0004930889,0.0005015867,0.001010103,0.0005554807,0.0008584506,0.0008954569,0.0006798374,0.0003608731],"category_scores_gemma":[0.005747161,0.000398893,0.0002247204,0.001129557,0.001157289,0.002234505,0.001097137,0.0003381199,0.0001316343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005663672,"about_ca_system_score_gemma":0.0003926662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009547813,"about_ca_topic_score_gemma":0.001274358,"domain_scores_codex":[0.9992409,0.0003198934,0.00003504742,0.00006145584,0.0002873832,0.00005531767],"domain_scores_gemma":[0.9978027,0.001320362,0.00042098,0.0002416125,0.0001769378,0.00003738945],"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":[0.00004884099,0.00001674702,0.001055476,0.0001096142,0.00003062974,0.0001259953,0.0001243873,0.9619827,0.006193346,0.008682359,0.0003775108,0.02125243],"study_design_scores_gemma":[0.00001668396,0.0001154563,0.0008738891,0.0000112983,0.00002157163,0.0002019401,0.00011793,0.9749138,0.002842549,0.01921644,0.001648842,0.00001959618],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2270947,0.003130933,0.7661594,0.0004841754,0.00004267292,0.0001062634,0.00009362664,0.0008555096,0.002032789],"genre_scores_gemma":[0.9405022,0.001775857,0.05667452,0.00007032368,0.00004353611,0.00007908251,0.00009558941,0.00004795073,0.0007108919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001569847,"threshold_uncertainty_score":0.008302271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01424154330528261,"score_gpt":0.2291245243339125,"score_spread":0.2148829810286299,"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."}}