{"id":"W2785073677","doi":"10.1007/s10569-017-9800-x","title":"Autonomous optical navigation using nanosatellite-class instruments: a Mars approach case study","year":2018,"lang":"en","type":"article","venue":"Celestial Mechanics and Dynamical Astronomy","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spacecraft; Star tracker; Extended Kalman filter; Computer science; Mars Exploration Program; Position (finance); Exploration of Mars; Orbital mechanics; Estimator; Orbital elements; Orbit determination; Celestial navigation; BitTorrent tracker; Kalman filter; Physics; Geodesy; Remote sensing; Artificial intelligence; Satellite; Astronomy; Geology; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004912836,0.0002766586,0.0001895238,0.0003846975,0.0006467184,0.0005534334,0.0005628405,0.0007904066,0.0007085621],"category_scores_gemma":[0.001194065,0.00009596779,0.0002363059,0.0004213387,0.0003518836,0.000609447,0.0006690804,0.000242162,0.0001708024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003788728,"about_ca_system_score_gemma":0.0002639515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005612878,"about_ca_topic_score_gemma":0.009776104,"domain_scores_codex":[0.9996845,0.0001006927,0.00001395867,0.00004854304,0.0001079388,0.00004436055],"domain_scores_gemma":[0.9993725,0.0002714436,0.00008175564,0.0001093788,0.0001158072,0.00004907722],"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":[0.001565014,0.001004233,0.08842487,0.0005444325,0.0002657655,0.005558252,0.002045796,0.543269,0.03483767,0.01131021,0.004522076,0.3066527],"study_design_scores_gemma":[0.0002473357,0.002657707,0.04932257,0.00007298515,0.0001445586,0.003134526,0.003045624,0.8569112,0.04474587,0.004969304,0.03465641,0.00009189947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9628347,0.0002586966,0.02579498,0.0002299658,0.00002429019,0.00008316403,0.0001547666,0.000183604,0.01043571],"genre_scores_gemma":[0.9849326,0.00008364451,0.01374565,0.00001951708,0.000007723066,0.00001900326,0.00007275101,0.00001406266,0.001105091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005612878,"threshold_uncertainty_score":0.01116043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084781157892619,"score_gpt":0.2242252153437815,"score_spread":0.2133774037648553,"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."}}