{"id":"W2316805689","doi":"10.4156/jdcta.vol5.issue4.19","title":"UAV Pose Estimation using POSIT Algorithm","year":2011,"lang":"en","type":"article","venue":"International Journal of Digital Content Technology and its Applications","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Estimation; Pose; Algorithm; Artificial intelligence; Computer vision","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003669634,0.00007932145,0.00009737971,0.0003697806,0.0000364352,0.00004577794,0.0001808129,0.00008257831,0.000007804389],"category_scores_gemma":[0.00002572374,0.00007551639,0.00003558745,0.0001495633,0.00004208471,0.0003560641,0.00002483813,0.0001141013,0.00000673719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004239102,"about_ca_system_score_gemma":0.00001275796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.898576e-7,"about_ca_topic_score_gemma":2.689095e-7,"domain_scores_codex":[0.9994391,0.000002706594,0.0002922528,0.00006939348,0.0001184326,0.00007807566],"domain_scores_gemma":[0.9993919,0.00001461445,0.0001057835,0.00006320081,0.0003841236,0.00004042574],"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":[0.00005139019,0.0004481142,0.00383544,0.00003158257,0.0008175478,0.0000627628,0.000317089,0.01892904,0.02638725,0.2912959,0.0001622947,0.6576616],"study_design_scores_gemma":[0.001175785,0.0002172007,0.001625102,0.0001262143,0.0001098997,0.001217086,0.0003894199,0.9217718,0.03160748,0.03847631,0.002888863,0.0003948307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1175257,0.0005305787,0.8803781,0.0002443107,0.0002109911,0.0001166827,0.0000271184,0.00008207271,0.0008844517],"genre_scores_gemma":[0.9896644,0.00009648019,0.0101146,0.00002277232,0.00005313596,0.000004936999,0.00001089207,0.00001114616,0.00002164348],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9028428,"threshold_uncertainty_score":0.3079469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0377648986128527,"score_gpt":0.2393552231191609,"score_spread":0.2015903245063082,"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."}}