{"id":"W3117881696","doi":"10.1109/iemcon51383.2020.9284856","title":"Detection of Long Narrow Landing Features for Autonomous UAV Perching","year":2020,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RANSAC; Point cloud; Computer science; Computer vision; Artificial intelligence; Position (finance); Perch; GRASP; Feature (linguistics); Line (geometry); Real-time computing; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00003584346,0.0000569597,0.00008083091,0.00002981152,0.00003277413,0.00001606834,0.00003275526,0.00004081044,0.0000104651],"category_scores_gemma":[0.00002646691,0.00005432393,0.00003692495,0.0000661908,0.000004404766,0.00004826605,0.000004207026,0.00004762482,0.000001861988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001882244,"about_ca_system_score_gemma":0.000003552024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001141192,"about_ca_topic_score_gemma":0.00001939995,"domain_scores_codex":[0.9996978,0.000005294923,0.00009913564,0.00006875801,0.00004590383,0.0000830754],"domain_scores_gemma":[0.9998658,0.00002655989,0.00001270004,0.00004267355,0.00001850939,0.00003371215],"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":[0.000007509126,0.000002513529,0.0001869963,0.000124289,0.00001123507,6.830811e-7,0.00038618,0.899716,0.09516206,0.0002782492,0.0001780568,0.003946205],"study_design_scores_gemma":[0.0001409336,0.00003662168,0.0006238641,0.000007177931,0.00000864731,0.000001376417,0.00006507079,0.8891619,0.1096694,0.0000235667,0.0001941719,0.0000672586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09836141,0.00006645128,0.9001192,0.0001203043,0.0001206716,0.0001072845,0.000002220508,0.0001785816,0.0009238029],"genre_scores_gemma":[0.9971511,0.000003946934,0.002645613,0.00004161928,0.00008344641,0.00000288119,0.000008218969,0.00001738058,0.00004579753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8987897,"threshold_uncertainty_score":0.2215266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409414496828751,"score_gpt":0.210153823838638,"score_spread":0.1960596788703504,"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."}}