{"id":"W4388926254","doi":"10.48550/arxiv.2311.11838","title":"Tensor-based Space Debris Detection for Satellite Mega-constellations","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Satellite Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Space debris; Satellite; Tensor (intrinsic definition); Constellation; Computer science; Spacecraft; Debris; Line-of-sight; Aerospace engineering; Remote sensing; Algorithm; Physics; Mathematics; Geology; Engineering; Geometry; Astronomy","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":[0.0004857539,0.0006234085,0.000470142,0.000702639,0.0003820762,0.0005403041,0.0005533258,0.0004176332,0.0006320782],"category_scores_gemma":[0.001720825,0.0001948458,0.0004121295,0.0006383348,0.0005604153,0.001340234,0.0008465322,0.0006029615,0.0002411686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003185384,"about_ca_system_score_gemma":0.0006023975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001966499,"about_ca_topic_score_gemma":0.002428055,"domain_scores_codex":[0.9995435,0.0001235663,0.00002040129,0.00007449883,0.0001734049,0.00006467757],"domain_scores_gemma":[0.9991558,0.0002265024,0.0001867267,0.0001149549,0.0002477194,0.0000682835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001056776,0.0001648414,0.01138274,0.0003175935,0.0001408535,0.0004135743,0.0004712755,0.2863847,0.1612788,0.01702801,0.004577497,0.5167834],"study_design_scores_gemma":[0.000005859193,0.00007096081,0.001035733,0.000005180789,0.00001517895,0.0001125173,0.00006177765,0.9843576,0.01138303,0.002322649,0.0006151477,0.00001431365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1136552,0.0003885193,0.8836168,0.0002590484,0.00007122724,0.00002880958,0.00007787901,0.0004175639,0.001485032],"genre_scores_gemma":[0.7872154,0.0003552235,0.2105686,0.00008454136,0.0000714893,0.00002766175,0.000192535,0.00003298494,0.001451708],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001966499,"threshold_uncertainty_score":0.003910065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1480864011917817,"score_gpt":0.2034254678770513,"score_spread":0.05533906668526969,"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."}}