{"id":"W4385297541","doi":"10.32920/23796126.v1","title":"Autonomous Recalibration of Star Trackers","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Inertial Sensor and Navigation","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Star tracker; Calibration; Computer science; Orbit (dynamics); BitTorrent tracker; Star (game theory); Field of view; Orbit determination; Interplanetary spaceflight; Remote sensing; Aerospace engineering; Artificial intelligence; Physics; Spacecraft; Engineering; Astrophysics; Eye tracking; Global Positioning System; Geography; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0008846632,0.0006789244,0.0007779511,0.0007545157,0.0005798831,0.0009429757,0.001295467,0.0005673846,0.001978943],"category_scores_gemma":[0.003036993,0.0004156449,0.0004616089,0.0007070162,0.0004529259,0.001091715,0.001307214,0.001038009,0.001536747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005379525,"about_ca_system_score_gemma":0.001195781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008246457,"about_ca_topic_score_gemma":0.01315823,"domain_scores_codex":[0.9989401,0.0001461371,0.00003468612,0.0003697848,0.0003771736,0.0001322918],"domain_scores_gemma":[0.99757,0.0003129674,0.000270891,0.001125051,0.0006088399,0.0001122612],"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":[0.0007357463,0.0003031329,0.05483927,0.0001471891,0.0001877319,0.0002897741,0.001019164,0.133294,0.08606509,0.002352449,0.01627738,0.7044891],"study_design_scores_gemma":[0.0001395451,0.0004715786,0.06699509,0.00003786869,0.00007929897,0.0005368516,0.0005229995,0.800613,0.09563477,0.003299232,0.03154228,0.0001275347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5191335,0.0003859679,0.4514796,0.0002427012,0.0002287313,0.0001928927,0.0006348345,0.01764107,0.01006067],"genre_scores_gemma":[0.866638,0.0001042718,0.1251603,0.0001388478,0.00006103505,0.00007134624,0.001723905,0.0008181186,0.00528408],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008246457,"threshold_uncertainty_score":0.01639688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02582507882420955,"score_gpt":0.2372453279333896,"score_spread":0.21142024910918,"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."}}