{"id":"W4376615795","doi":"10.1002/sat.1482","title":"Machine Learning and Deep Learning powered satellite communications: Enabling technologies, applications, open challenges, and future research directions","year":2023,"lang":"en","type":"article","venue":"International Journal of Satellite Communications and Networking","topic":"Satellite Communication Systems","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Communications satellite; Satellite; Telecommunications; Open research; Popularity; Constellation; Deep learning; NASA Deep Space Network; Artificial intelligence; Spacecraft; World Wide Web; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003324248,0.0002517521,0.0003959541,0.0009606765,0.0009623168,0.000579219,0.002814351,0.0002106289,0.000004213213],"category_scores_gemma":[0.00009615761,0.0002601051,0.00006228223,0.0009410916,0.0004630816,0.0005711818,0.002760629,0.001657302,0.00001087212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001543629,"about_ca_system_score_gemma":0.00003385244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003160953,"about_ca_topic_score_gemma":0.000122496,"domain_scores_codex":[0.9972869,0.000713861,0.0009368092,0.000278818,0.0004275637,0.0003560738],"domain_scores_gemma":[0.9956189,0.001885785,0.0003905089,0.001219582,0.0007524543,0.0001327786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001689701,0.00003220338,0.00294295,0.00004379556,0.0001982252,0.000003431126,0.001877757,0.000002268253,0.000262812,0.005113077,0.00000113349,0.9895055],"study_design_scores_gemma":[0.0004074333,0.00004711347,0.001359097,0.0004015019,0.00002514568,0.0002119282,0.006989407,0.002719518,0.00001078551,0.001876629,0.9857196,0.0002319089],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001338777,0.9878854,0.00003594614,0.004158549,0.000261508,0.0004272529,0.000005619854,0.0003586473,0.006733221],"genre_scores_gemma":[0.09429402,0.9004104,0.00463339,0.00001815135,0.0002718131,0.0001134987,0.0001098551,0.00005992549,0.0000889197],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9892735,"threshold_uncertainty_score":0.9999851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1094231379604652,"score_gpt":0.363805857677649,"score_spread":0.2543827197171838,"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."}}