{"id":"W2934185291","doi":"10.1109/tgcn.2019.2909140","title":"Green Data-Collection From Geo-Distributed IoT Networks Through Low-Earth-Orbit Satellites","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Green Communications and Networking","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Wuhan University; University of Science and Technology of China; National Natural Science Foundation of China; Australian National University; University of Ottawa","keywords":"Astrobiology; Orbit (dynamics); Remote sensing; Internet of Things; Low earth orbit; Earth observation; Planet; Earth (classical element); Computer science; Satellite; Astronomy; Geodesy; Geology; Aerospace engineering; Physics; Engineering; World Wide Web","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005162435,0.0005166967,0.0004974012,0.0003009731,0.0007078892,0.0007226095,0.000580131,0.0003298844,0.0004698533],"category_scores_gemma":[0.0009956904,0.0002178502,0.0003068542,0.000561677,0.0005034826,0.0008721818,0.0008050009,0.0004587268,0.0000774908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008672485,"about_ca_system_score_gemma":0.001087849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005679414,"about_ca_topic_score_gemma":0.009131279,"domain_scores_codex":[0.9997615,0.00007209524,0.00001129059,0.00004045577,0.00006818404,0.00004643752],"domain_scores_gemma":[0.9995121,0.0002530122,0.00007196613,0.00004727826,0.00007001081,0.00004556494],"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":[0.0001165782,0.00008241642,0.001757256,0.00009364833,0.00002675496,0.0001741224,0.0001557554,0.928441,0.008776083,0.008753364,0.001618568,0.05000435],"study_design_scores_gemma":[0.000007520321,0.00002505765,0.0002975129,0.000003711726,0.00000613504,0.0000174727,0.000056881,0.9950868,0.001924218,0.002139018,0.0004306297,0.00000494042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2215163,0.0006992117,0.7696184,0.0006841814,0.00008294326,0.0001239135,0.00008486649,0.0007455345,0.00644474],"genre_scores_gemma":[0.9697137,0.0001719708,0.02911755,0.00006270095,0.00001711758,0.00004115151,0.00004522779,0.00002063718,0.0008099386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005679414,"threshold_uncertainty_score":0.01129276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03673713021773674,"score_gpt":0.256749679795174,"score_spread":0.2200125495774373,"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."}}