{"id":"W1919870441","doi":"10.1109/melcon.1994.380997","title":"Robotics and structural dynamics characterization of the space station remote manipulator system using photogrammetric techniques","year":2002,"lang":"en","type":"article","venue":"","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Photogrammetry; Artificial intelligence; Camera resectioning; Computer vision; Calibration; Computer science; Camera auto-calibration; Robotics; Lens (geology); Nonlinear system; Tilt (camera); Computer graphics (images); Robot; Mathematics; Physics; Optics; Geometry","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":[0.0001072542,0.0004368498,0.0002088821,0.0009690393,0.0002851248,0.000348884,0.0003123406,0.0003327645,0.003498755],"category_scores_gemma":[0.0003719729,0.0001996465,0.0002216029,0.0002994738,0.0003381312,0.0004578441,0.0002052154,0.0002249764,0.0006509862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003532491,"about_ca_system_score_gemma":0.0003837975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003230889,"about_ca_topic_score_gemma":0.003914301,"domain_scores_codex":[0.9998827,0.00001294802,0.000004235535,0.00002662322,0.00006484393,0.000008526685],"domain_scores_gemma":[0.9999071,0.00002348724,0.00002964852,0.00001053167,0.00002284157,0.0000062851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001060538,0.0000824719,0.006216819,0.0002409333,0.00003495405,0.000484383,0.0002749399,0.612357,0.1801273,0.0236408,0.001248445,0.1751859],"study_design_scores_gemma":[0.00001463192,0.000211541,0.01536413,0.00003075056,0.00001305111,0.0004044254,0.0001222975,0.9611024,0.01279853,0.005073139,0.004829922,0.00003525004],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2488999,0.0008442481,0.7319796,0.0003417759,0.00002416286,0.00011605,0.0003925553,0.0006669998,0.01673468],"genre_scores_gemma":[0.904123,0.0007311535,0.08491861,0.0000267748,0.00003779505,0.0001373379,0.0003976356,0.00003597217,0.009591703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003498755,"threshold_uncertainty_score":0.0117045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03945579131121415,"score_gpt":0.243555038437778,"score_spread":0.2040992471265638,"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."}}