{"id":"W2064883213","doi":"10.1117/12.472603","title":"<title>Imaging and tracking elements of the International Space Station using a 3D autosynchronized scanner</title>","year":2002,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Planetary Science and Exploration","field":"Physics and Astronomy","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Neptec Design Group (Canada)","funders":"","keywords":"International Space Station; Raster graphics; Computer vision; Centroid; Computer science; Scanner; Space Shuttle; Computer graphics (images); Artificial intelligence; Tracking (education); Laser scanning; Raster scan; Remote sensing; Engineering; Laser; Optics; Geography; Physics; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001809075,0.0001028961,0.0001159394,0.00004272016,0.00005324241,0.00006081422,0.0002817484,0.00002979285,0.0001171762],"category_scores_gemma":[0.00004659517,0.00008076421,0.0001188318,0.0001222889,0.00007809033,0.0003589228,0.00005694283,0.00009071741,0.000004933203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004533238,"about_ca_system_score_gemma":0.00001481494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005556429,"about_ca_topic_score_gemma":1.019902e-7,"domain_scores_codex":[0.9991633,2.118265e-8,0.0002423602,0.0001399723,0.0003214638,0.0001328449],"domain_scores_gemma":[0.9994124,0.00002496933,0.0001946149,0.00002663694,0.0003111311,0.00003023851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001778221,0.00008976313,0.004567028,0.000116596,0.0002650111,5.109348e-8,0.0004504,0.0004629683,0.6017343,0.3753586,0.01164959,0.005287905],"study_design_scores_gemma":[0.0008804452,0.0000577125,0.001746579,0.0003084924,0.0001236554,0.000005795059,0.0007467187,0.939182,0.03079708,0.002219077,0.0236322,0.0003002101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881759,0.00005483782,0.0001838598,0.0007654242,0.0002304341,0.0001485199,0.00004127615,0.0000142619,0.01038554],"genre_scores_gemma":[0.9767991,0.00002468658,0.02246623,0.0000329628,0.0002731225,0.000009899717,0.00001525694,0.00001532851,0.0003634538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9387191,"threshold_uncertainty_score":0.3293469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323398914911459,"score_gpt":0.2205616626590005,"score_spread":0.2073276735098859,"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."}}