{"id":"W4380996230","doi":"10.3390/s23125581","title":"Scheduling Sparse LEO Satellite Transmissions for Remote Water Level Monitoring","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Satellite; Computer science; Scheduling (production processes); Constellation; Low earth orbit; Real-time computing; Satellite constellation; Energy consumption; Communications satellite; Wireless; Wireless sensor network; Remote sensing; Computer network; Telecommunications; Engineering; Electrical engineering; Aerospace engineering; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001848287,0.0001410961,0.0001424213,0.00007636034,0.0001172952,0.00003619783,0.00008581104,0.0001009541,0.00001823714],"category_scores_gemma":[0.000009128838,0.0001146727,0.00009178784,0.0001484813,0.00001081653,0.00004758803,0.000011419,0.0001439876,0.0001950314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002099064,"about_ca_system_score_gemma":0.000004861889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006120986,"about_ca_topic_score_gemma":0.000001749953,"domain_scores_codex":[0.9991044,0.00001263209,0.0001788421,0.0001519455,0.00009306837,0.0004591093],"domain_scores_gemma":[0.9996524,0.00006220239,0.00000844657,0.0001659936,0.00002291622,0.00008801091],"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":[0.00002632828,0.000004378171,0.0001283957,0.0002169216,0.00004922596,0.00001989076,0.001203392,0.8690618,0.04530397,0.00006049618,0.0003282885,0.08359686],"study_design_scores_gemma":[0.0006022839,0.00003190848,0.0008488801,0.0003035523,0.00002333276,0.000005360436,0.0001724129,0.6219235,0.220252,0.001699349,0.1536962,0.0004412605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774414,0.0001809821,0.01363637,0.0003121616,0.001451445,0.003678762,0.00001905442,0.001360558,0.001919217],"genre_scores_gemma":[0.9734316,0.0003074706,0.02062474,0.00001899055,0.001429226,0.0003500643,0.00003089381,0.0001480051,0.003659032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2471383,"threshold_uncertainty_score":0.4676215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08195112128001246,"score_gpt":0.2954840789622386,"score_spread":0.2135329576822261,"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."}}