{"id":"W3141185698","doi":"10.1109/iccspa49915.2021.9385709","title":"Visual Heading Estimation for UAVs in Indoor Environments","year":2021,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Drone; Computer science; Heading (navigation); Artificial intelligence; Real-time computing; Computer vision; Lidar; GNSS applications; Global Positioning System; Remote sensing; Engineering; Aerospace engineering; Geography","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":[0.0000265716,0.00004597681,0.00005724542,0.00003372403,0.00001459574,0.0000154682,0.00001488225,0.00003409237,0.00003762565],"category_scores_gemma":[0.00001757101,0.00005082025,0.00001470696,0.0000640002,0.000002940411,0.0000527023,0.000004442626,0.00002608569,0.0000136108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000482611,"about_ca_system_score_gemma":0.000004438279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002713208,"about_ca_topic_score_gemma":0.00001215005,"domain_scores_codex":[0.9996846,0.000005211267,0.0001040704,0.0000687693,0.00004794187,0.0000894035],"domain_scores_gemma":[0.9999031,0.00002341927,0.000005750923,0.0000443667,0.000004205938,0.00001917871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001977689,0.00001623446,0.0008217558,0.00002134604,0.000004160017,0.000001829853,0.00004164954,0.9825608,0.009564692,0.0008374621,0.00008609647,0.006041986],"study_design_scores_gemma":[0.0002459795,0.00001110162,0.001302492,0.000009777359,0.000002411137,6.400774e-7,0.00002523801,0.9648023,0.03288968,0.0001516519,0.0004989674,0.00005975139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1437517,0.00002837456,0.8553697,0.00003855457,0.00008646064,0.00007762459,0.000001044203,0.00003275345,0.0006137016],"genre_scores_gemma":[0.9859504,0.00001412156,0.01372275,0.00004446087,0.00001751718,0.000008771156,0.00005664552,0.00001292969,0.0001724754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8421986,"threshold_uncertainty_score":0.207239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008374461359967495,"score_gpt":0.2318876095353371,"score_spread":0.2235131481753696,"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."}}