{"id":"W4400720244","doi":"10.1016/j.measurement.2024.115340","title":"Unmanned aerial vehicle (UAV) based measurements","year":2024,"lang":"en","type":"article","venue":"Measurement","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Remote sensing; Drone; Environmental science; Remotely operated underwater vehicle; Aerospace engineering; Marine engineering; Computer science; Aeronautics; Engineering; Artificial intelligence; Geology; Mobile robot; Robot","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008563207,0.0001431405,0.000101446,0.00003761245,0.0001574731,0.0001051864,0.0001668802,0.00004812927,0.001147211],"category_scores_gemma":[0.00003649765,0.0001276309,0.00008018409,0.0002901576,0.00006748932,0.000079739,0.0000431112,0.0001048834,0.003331739],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005200036,"about_ca_system_score_gemma":0.0000423131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002520615,"about_ca_topic_score_gemma":0.0001556479,"domain_scores_codex":[0.9979818,0.00006763545,0.0001944318,0.0003846333,0.001093421,0.0002780176],"domain_scores_gemma":[0.9994814,0.00001272738,0.00002482724,0.0003425152,0.00002261155,0.0001158901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004537246,0.0002700597,0.002931888,0.00004385539,0.00006973954,0.00001362544,0.000355795,0.003889501,0.8053473,0.0001270846,0.07974312,0.1071627],"study_design_scores_gemma":[0.0009736834,0.0001320084,0.02615416,0.0001608469,0.0001020304,0.000005620821,0.00003991833,0.03454006,0.1558285,0.00070447,0.7807558,0.0006029439],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5358379,0.0009993159,0.04431314,0.01275196,0.004135608,0.00216142,0.00002065715,0.001886268,0.3978938],"genre_scores_gemma":[0.9976381,0.000001724158,0.001401,0.0002976132,0.0001290394,0.00001368107,0.000004763547,0.00002392301,0.0004901389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7010126,"threshold_uncertainty_score":0.9997659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05132166779256354,"score_gpt":0.2500984269131628,"score_spread":0.1987767591205993,"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."}}