{"id":"W2071238267","doi":"10.1109/imvip.2007.2","title":"A Dynamics Estimation Filter for Pose and Motion Estimation in Orbit","year":2007,"lang":"en","type":"article","venue":"","topic":"Space Satellite Systems and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Rendezvous; Computer science; Computer vision; Kalman filter; Extended Kalman filter; Spacecraft; Snapshot (computer storage); Artificial intelligence; Pose; Motion estimation; Filter (signal processing); Orbit (dynamics); Control theory (sociology); Engineering; Aerospace engineering","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":[0.0004686335,0.0006862186,0.0006939089,0.0005903603,0.0006320062,0.0006480931,0.000642948,0.0008695766,0.004850526],"category_scores_gemma":[0.001568908,0.0003733602,0.0005025223,0.0006319724,0.0002489428,0.0009950318,0.0004879683,0.0009687593,0.002996325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005356462,"about_ca_system_score_gemma":0.001308477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01586066,"about_ca_topic_score_gemma":0.01532268,"domain_scores_codex":[0.9995425,0.00004398248,0.00002427711,0.0001489924,0.0002044493,0.00003574479],"domain_scores_gemma":[0.9997025,0.00006498273,0.00002910532,0.00003399137,0.0001579102,0.00001151477],"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":[0.0002338787,0.00009890381,0.001004098,0.0001918714,0.0001173645,0.0001498435,0.0001146789,0.08956522,0.03959649,0.02213954,0.01233946,0.8344486],"study_design_scores_gemma":[0.00006217492,0.0001841044,0.002246188,0.00004301588,0.0000729598,0.0002421914,0.00002245252,0.9251783,0.0170512,0.005349965,0.04949524,0.00005216614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00139143,0.0001964612,0.9968001,0.000056213,0.00009681404,0.00002065783,0.00009162384,0.0005886335,0.0007580784],"genre_scores_gemma":[0.1450767,0.001513697,0.8262095,0.0003025846,0.00035258,0.0003503494,0.001616354,0.0002196258,0.02435856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01586066,"threshold_uncertainty_score":0.0315367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005135587741352846,"score_gpt":0.2168248499680421,"score_spread":0.2116892622266893,"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."}}