{"id":"W4413385634","doi":"10.1007/s11432-024-4523-1","title":"Split-LEO: efficient AI model training over LEO satellite networks","year":2025,"lang":"en","type":"article","venue":"Science China Information Sciences","topic":"Satellite Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Training (meteorology); Satellite; Computer science; Artificial intelligence; Geography; Meteorology; Engineering; 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":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005695685,0.000672598,0.0005332024,0.0003079371,0.0004388838,0.0005191606,0.001020922,0.0005878651,0.005260773],"category_scores_gemma":[0.00194368,0.0002924298,0.0002465509,0.0004317424,0.0002992118,0.001108832,0.001211727,0.001485671,0.000987965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004170215,"about_ca_system_score_gemma":0.001036224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01209332,"about_ca_topic_score_gemma":0.01782876,"domain_scores_codex":[0.9997898,0.00005028131,0.00001024917,0.00004045738,0.00005264543,0.00005656644],"domain_scores_gemma":[0.9993975,0.0003133226,0.00002979803,0.0000913246,0.0001207106,0.0000473193],"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":[0.0008246885,0.0002307047,0.001320432,0.00007481925,0.0000832517,0.00016797,0.0001149562,0.5578387,0.008516568,0.005388011,0.01088433,0.4145555],"study_design_scores_gemma":[0.000007819102,0.00001346888,0.00005068622,9.781221e-7,0.000002235038,0.000005694211,0.00000643941,0.9985,0.0005924359,0.000573221,0.0002454601,0.000001576956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06444336,0.0003197732,0.9220744,0.0003793704,0.0001402864,0.00007830537,0.0003039998,0.005450274,0.006810179],"genre_scores_gemma":[0.780956,0.0001422099,0.2077798,0.0003033832,0.00008349208,0.0001355192,0.0009783427,0.000260886,0.009360279],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01209332,"threshold_uncertainty_score":0.02404583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099188425250977,"score_gpt":0.2885848134555221,"score_spread":0.2675929292030123,"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."}}