{"id":"W2155369754","doi":"10.5194/isprsarchives-xl-3-w1-123-2014","title":"Mapping with MAV: Experimental Study on the Contribution of Absolute and Relative Aerial Position Control","year":2014,"lang":"en","type":"article","venue":"˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Gimbal; Computer science; GNSS applications; Context (archaeology); Global Positioning System; Antenna (radio); Photogrammetry; Computer vision; Artificial intelligence; Engineering; Geography; Telecommunications; Aerospace engineering","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":[0.0005418212,0.0004786888,0.0004165779,0.0004547769,0.0003732045,0.0006259087,0.0006110039,0.0006759926,0.001822349],"category_scores_gemma":[0.002529114,0.0001419208,0.0001783082,0.0004496655,0.0003953965,0.0008664919,0.0007370218,0.0004467945,0.000358431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001397222,"about_ca_system_score_gemma":0.0002018284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009812639,"about_ca_topic_score_gemma":0.0006956304,"domain_scores_codex":[0.9993992,0.0001700204,0.00002673621,0.0001646364,0.0001387568,0.0001007141],"domain_scores_gemma":[0.9985083,0.0006700678,0.0001096312,0.0004078163,0.0002201855,0.00008404064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003677592,0.002930128,0.01858774,0.0006653103,0.0001829199,0.0005308806,0.001449099,0.1017741,0.6790304,0.002960949,0.00114169,0.1870692],"study_design_scores_gemma":[0.0002141193,0.01298554,0.05334011,0.00008329943,0.0001528011,0.0008126766,0.001941483,0.5409167,0.3799023,0.003091364,0.006426454,0.0001331494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817404,0.0001350425,0.01550186,0.00003313555,0.00003560707,0.00003443788,0.0001125814,0.0002102642,0.002196755],"genre_scores_gemma":[0.9924446,0.00003798496,0.00672739,0.00001350414,0.000006610666,0.00002367958,0.0001519362,0.00003796641,0.000556402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001822349,"threshold_uncertainty_score":0.006096363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155841139608628,"score_gpt":0.229785508467082,"score_spread":0.2182270970709957,"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."}}