{"id":"W2041798060","doi":"10.1109/mwc.2010.5490984","title":"CORE: a coding-aware opportunistic routing mechanism for wireless mesh networks [Accepted from Open Call","year":2010,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nokia (Canada)","funders":"","keywords":"Computer science; Computer network; Wireless mesh network; Linear network coding; Routing protocol; Distributed computing; Dynamic Source Routing; Network packet; Virtual routing and forwarding; Packet forwarding; Wireless network; Wireless; Telecommunications","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":[0.001074483,0.0003318675,0.0003501202,0.0006996798,0.000525682,0.0007226807,0.001415602,0.000654808,0.001787952],"category_scores_gemma":[0.002024023,0.0001745289,0.000290307,0.0005867525,0.0007795417,0.00143281,0.001193488,0.0008001229,0.0003768388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004654737,"about_ca_system_score_gemma":0.0005699943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008976361,"about_ca_topic_score_gemma":0.001263925,"domain_scores_codex":[0.9996672,0.00008144708,0.00002176846,0.00004612749,0.0001391412,0.00004424246],"domain_scores_gemma":[0.9992562,0.0002515246,0.00009965675,0.0001598938,0.0001899451,0.00004267328],"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":[0.0004183837,0.0001416575,0.001011006,0.0004383595,0.0001373323,0.0005898507,0.0004926263,0.09456183,0.08771713,0.2689919,0.03072574,0.5147742],"study_design_scores_gemma":[0.00008298188,0.0003624975,0.0007805421,0.00009051567,0.0001007512,0.001081659,0.0001203913,0.7932231,0.02894851,0.07026011,0.104828,0.0001210107],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01707381,0.0009055652,0.9720163,0.0004944993,0.0003621545,0.0001275995,0.00009913879,0.001468287,0.007452625],"genre_scores_gemma":[0.6210204,0.001910329,0.3617398,0.0007783556,0.0004845849,0.0003186136,0.0005111597,0.0003224216,0.01291435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001787952,"threshold_uncertainty_score":0.005981326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.137312499980837,"score_gpt":0.3460634148860505,"score_spread":0.2087509149052135,"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."}}