{"id":"W156557657","doi":"","title":"3D LASSO: REAL-TIME POSE ESTIMATION FROM 3D DATA FOR AUTONOMOUS SATELLITE SERVICING","year":2005,"lang":"en","type":"article","venue":"ESASP","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer vision; Computer science; Pose; Artificial intelligence; Spacecraft; Iterative closest point; Point cloud; Real-time computing; Engineering; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006677541,0.001021295,0.0006361966,0.000626088,0.0003502622,0.0006314814,0.0008452784,0.0006460241,0.003424077],"category_scores_gemma":[0.001065463,0.0004508191,0.0005439298,0.0005583399,0.0004243216,0.0007414751,0.001110392,0.0009065156,0.001827625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229227,"about_ca_system_score_gemma":0.0005244184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002335847,"about_ca_topic_score_gemma":0.004069807,"domain_scores_codex":[0.999377,0.0001021087,0.00002368428,0.0001215793,0.0003327455,0.00004290075],"domain_scores_gemma":[0.9997019,0.00007385791,0.00006393992,0.00006603429,0.0000630584,0.00003111817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004726656,0.0001410037,0.002152565,0.0001906042,0.0001010327,0.0003021126,0.0002157646,0.06112179,0.1359619,0.003558568,0.02038964,0.7753924],"study_design_scores_gemma":[0.00003975193,0.0001667994,0.002680714,0.00002716742,0.00001186354,0.0003288971,0.00007853195,0.9398669,0.03609307,0.002293364,0.01836178,0.00005114169],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01028527,0.0002111144,0.9823775,0.0001099719,0.00005947383,0.00007108127,0.0003554654,0.00541873,0.001111448],"genre_scores_gemma":[0.10933,0.0002991768,0.8829897,0.0001958735,0.00006842359,0.0002813349,0.002583685,0.0006287977,0.003622904],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003424077,"threshold_uncertainty_score":0.0114547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667910877750263,"score_gpt":0.2373326360455761,"score_spread":0.2206535272680735,"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."}}