{"id":"W4384557888","doi":"10.3390/rs15143558","title":"UAV-Based Computer Vision System for Orchard Apple Tree Detection and Health Assessment","year":2023,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"A&L Canada Laboratories (Canada); Concordia University; Lakehead University; University of New Brunswick; Université TÉLUQ; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orchard; Computer science; Tree health; Robustness (evolution); Tree (set theory); Artificial intelligence; RGB color model; Computer vision; Machine learning; 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":[0.0005482477,0.0001170322,0.0001604555,0.00006438021,0.000425661,0.00005798589,0.00004280884,0.00005369024,0.000001518215],"category_scores_gemma":[0.000004474721,0.0001126737,0.00005045488,0.0003029123,0.00005160035,0.00004278798,0.00005134464,0.00008356165,0.00006448656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003251041,"about_ca_system_score_gemma":0.00001861058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005788797,"about_ca_topic_score_gemma":0.000238587,"domain_scores_codex":[0.9989173,0.00006148398,0.0001991755,0.000356897,0.0001958067,0.0002693552],"domain_scores_gemma":[0.999477,0.00007883338,0.00009364219,0.0002328276,0.00001148592,0.0001061668],"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":[0.000007099927,0.000005178488,0.00001227329,0.0000513497,0.000004116016,0.000002019321,0.0001088017,0.004255582,0.02586304,0.000006514878,0.0009134282,0.9687706],"study_design_scores_gemma":[0.0003046963,0.0001050448,0.003112909,0.00007618268,0.000007497284,0.00002404203,0.0001119575,0.9845498,0.002101791,0.00004966067,0.009440859,0.0001155478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1818124,0.000006045962,0.8149365,0.001473518,0.0001943819,0.0005505337,0.000004102496,0.0003206856,0.0007018639],"genre_scores_gemma":[0.8894821,0.000004601241,0.1100868,0.0001796929,0.0001096234,6.838894e-8,0.0000261769,0.00002375814,0.00008719757],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9802942,"threshold_uncertainty_score":0.4594698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179918308147848,"score_gpt":0.2975262544088618,"score_spread":0.2757270713273833,"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."}}