{"id":"W4399567602","doi":"10.1145/3631726.3631731","title":"Adaptive Virtual Carrier Sense in Underwater Broadcasting","year":2023,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Broadcasting (networking); Sense (electronics); Computer science; Underwater; Sense of presence; Underwater acoustic communication; Telecommunications; Computer network; Virtual reality; Electrical engineering; Human–computer interaction; Engineering; Geology","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":[0.0001409516,0.00008744672,0.0001026153,0.0001157873,0.00003229068,0.00003008033,0.00008640977,0.00004858243,0.00004949143],"category_scores_gemma":[0.00000113047,0.00007870114,0.00002647388,0.0003025381,0.00001299905,0.00008506746,0.00005955207,0.0001082022,0.0003787472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004612002,"about_ca_system_score_gemma":0.000005800276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001189111,"about_ca_topic_score_gemma":0.0001713766,"domain_scores_codex":[0.9993851,0.00003333206,0.0001834568,0.00009685633,0.00009001563,0.0002112485],"domain_scores_gemma":[0.9996979,0.00004881299,0.000008970163,0.000188806,0.0000144542,0.000041109],"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":[0.00008602874,0.0000796687,0.01128741,0.0001590604,0.0003167982,0.0003175061,0.03590224,0.595067,0.2121063,0.005346968,0.009582346,0.1297487],"study_design_scores_gemma":[0.0009312814,0.00006237723,0.006492179,0.00009921732,0.000006979411,0.00003265337,0.01391586,0.9094001,0.02897126,0.0008257637,0.0386529,0.0006094011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9562532,0.00004818056,0.01761436,0.0001388501,0.0001033163,0.0001408002,0.000005963586,0.001049534,0.02464576],"genre_scores_gemma":[0.9974512,0.00001642354,0.0003100045,0.00003801567,0.00003173734,0.00001624055,0.000006264918,0.00002443594,0.002105606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3143331,"threshold_uncertainty_score":0.4868155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03101365849821286,"score_gpt":0.2276603052030995,"score_spread":0.1966466467048866,"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."}}