{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001235469,0.0003732526,0.0004959979,0.0007938521,0.0002693263,0.001699006,0.0004862997,0.001205888,0.004194168],"category_scores_gemma":[0.001562956,0.0001804635,0.0004222637,0.001291412,0.0007097161,0.002872576,0.0008366634,0.002007969,0.0009981033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006865342,"about_ca_system_score_gemma":0.001456994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001198479,"about_ca_topic_score_gemma":0.001388431,"domain_scores_codex":[0.9996868,0.00008433698,0.00002241598,0.00004733566,0.0001086266,0.00005041383],"domain_scores_gemma":[0.9987401,0.0007332753,0.00008469763,0.00004142409,0.0003071625,0.00009330166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006835712,0.00008405448,0.0008945296,0.006188785,0.00006860798,0.0001656675,0.000199365,0.003443899,0.001608028,0.1052173,0.04212223,0.8399392],"study_design_scores_gemma":[0.00001312029,0.00021904,0.001447031,0.006077414,0.00007748048,0.0005057019,0.0004972031,0.008187439,0.001923354,0.08966134,0.8913419,0.00004900218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001959438,0.9676822,0.006842198,0.01177032,0.001191749,0.00001432609,0.00007187911,0.0000562415,0.01041156],"genre_scores_gemma":[0.01749748,0.9726035,0.003561683,0.001753201,0.001418334,0.00002086952,0.00008322513,0.0000109386,0.003050695],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004194168,"threshold_uncertainty_score":0.01403087,"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."}}