{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000375924,0.00102106,0.0007756315,0.000946272,0.0004858042,0.0008901465,0.0006680055,0.000557917,0.003348014],"category_scores_gemma":[0.001275623,0.0003816246,0.0005272007,0.0005417678,0.0004364596,0.0007264405,0.001150894,0.0005994967,0.00185966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003442179,"about_ca_system_score_gemma":0.001099283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002145349,"about_ca_topic_score_gemma":0.002477188,"domain_scores_codex":[0.9995899,0.00006300979,0.00002028579,0.0001269474,0.0001620478,0.00003791157],"domain_scores_gemma":[0.999566,0.00008249175,0.00007030403,0.00006605479,0.0001884021,0.0000267173],"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":[0.0002850507,0.00006614669,0.003389919,0.0001688413,0.00005564806,0.0001674738,0.0002025497,0.2033243,0.028786,0.008360885,0.006033622,0.7491595],"study_design_scores_gemma":[0.00003728987,0.0001742161,0.001036113,0.0000192086,0.00001847598,0.0002634953,0.00008294346,0.9754546,0.0145128,0.002451092,0.005924835,0.00002499928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007818103,0.00008125394,0.9889836,0.00002790604,0.00003904947,0.00004665474,0.00005395162,0.001301987,0.001647543],"genre_scores_gemma":[0.273738,0.0002691865,0.7192565,0.00007822934,0.00004836085,0.0002156933,0.0007032148,0.0001810098,0.005509736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003348014,"threshold_uncertainty_score":0.01120025,"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."}}