{"id":"W2321230340","doi":"10.2514/6.2010-8152","title":"A Focusing Procedure for Nanosatellite Star Trackers","year":2010,"lang":"en","type":"article","venue":"AIAA Guidance, Navigation, and Control Conference","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"University of Toronto","keywords":"Star (game theory); BitTorrent tracker; Star tracker; Computer science; Aerospace engineering; Artificial intelligence; Engineering; Physics; Eye tracking; Astrophysics; Spacecraft","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":[0.0003645414,0.0002964188,0.0001862991,0.0003757086,0.0004615198,0.0002948798,0.00036602,0.0003926846,0.001675855],"category_scores_gemma":[0.0007286085,0.0002694273,0.0001970093,0.0003140952,0.0003969668,0.0003544439,0.0004609944,0.0003976359,0.0006639178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005523531,"about_ca_system_score_gemma":0.0005601267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000953723,"about_ca_topic_score_gemma":0.001759471,"domain_scores_codex":[0.9996448,0.00002990426,0.0000198235,0.0000754662,0.0002082282,0.00002184773],"domain_scores_gemma":[0.9995313,0.00007141446,0.00008414312,0.0001306509,0.000160853,0.00002167496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001387567,0.00006940658,0.002332129,0.0001386565,0.00002025404,0.0001256913,0.0002807762,0.009037303,0.8409203,0.01525906,0.001703945,0.1299737],"study_design_scores_gemma":[0.00004679563,0.0005025199,0.005599985,0.00002430514,0.00001478422,0.0008895901,0.00007231899,0.06848673,0.896367,0.003578792,0.02433274,0.00008450754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0865977,0.0002257781,0.9068967,0.0001745808,0.00006770249,0.0001835514,0.0001470335,0.0009833052,0.004723609],"genre_scores_gemma":[0.3046117,0.0002168327,0.6878873,0.0001383401,0.00002009003,0.0001951559,0.0001984701,0.0001124077,0.006619757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001675855,"threshold_uncertainty_score":0.005606234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009530082714640595,"score_gpt":0.2398285256826225,"score_spread":0.2302984429679819,"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."}}