{"id":"W2884476732","doi":"10.1109/jsen.2018.2857621","title":"Autonomous Recalibration of Star Trackers","year":2018,"lang":"en","type":"article","venue":"IEEE Sensors Journal","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Star tracker; Calibration; Computer science; BitTorrent tracker; Orbit (dynamics); Star (game theory); Field of view; Remote sensing; Aerospace engineering; Artificial intelligence; Engineering; Physics; Spacecraft; Eye tracking; Astrophysics","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":[0.0007797,0.0006590258,0.000744716,0.0007151033,0.0006266034,0.0008856956,0.001261683,0.0005618302,0.001681468],"category_scores_gemma":[0.002599694,0.0004061052,0.0004306764,0.0005917357,0.0004376608,0.001033448,0.001227261,0.001005903,0.001292324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005329456,"about_ca_system_score_gemma":0.001155657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007751516,"about_ca_topic_score_gemma":0.01287954,"domain_scores_codex":[0.9991164,0.000117316,0.0000296657,0.0002870817,0.0003328673,0.0001166963],"domain_scores_gemma":[0.9977502,0.0003023366,0.0002580856,0.0009401916,0.0006415935,0.0001075702],"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":[0.0007747341,0.0003465772,0.05615222,0.0001498926,0.000189661,0.0003248539,0.001111114,0.1577321,0.10478,0.002241998,0.01298807,0.6632087],"study_design_scores_gemma":[0.0001435693,0.0005603119,0.06199045,0.00004083889,0.00008231371,0.0005558087,0.0005296411,0.7939895,0.1072346,0.002788637,0.03194001,0.0001444025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5287586,0.0003982631,0.4464855,0.0002224144,0.0002085372,0.0001926416,0.0004537307,0.01416989,0.009110392],"genre_scores_gemma":[0.8819415,0.0001026224,0.1112497,0.000129287,0.00005025452,0.00006290843,0.001200528,0.0006621758,0.00460104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007751516,"threshold_uncertainty_score":0.01541281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108950877843457,"score_gpt":0.2245782717919071,"score_spread":0.2134887630134726,"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."}}