{"id":"W4304775501","doi":"10.3390/plants11202691","title":"UAV Image-Based Crop Growth Analysis of 3D-Reconstructed Crop Canopies","year":2022,"lang":"en","type":"article","venue":"Plants","topic":"Crop Yield and Soil Fertility","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Saskatchewan","funders":"Saskatchewan Pulse Growers; Canada First Research Excellence Fund; University of Saskatchewan","keywords":"Growing season; Biomass (ecology); Crop; Vegetation (pathology); Environmental science; Biomass partitioning; Volume (thermodynamics); Standing crop; Remote sensing; Agronomy; Biology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001310999,0.0004497476,0.0002566387,0.0017793,0.0001398969,0.0003604527,0.0002408917,0.0001879409,0.001371489],"category_scores_gemma":[0.0002886711,0.0001752822,0.0004325684,0.0008984889,0.00009391635,0.0002326305,0.0002051919,0.0002167221,0.000466928],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003042404,"about_ca_system_score_gemma":0.0002269207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01214679,"about_ca_topic_score_gemma":0.01962133,"domain_scores_codex":[0.9999272,0.00000691925,0.000003595731,0.00002275947,0.00002492611,0.00001468865],"domain_scores_gemma":[0.9998622,0.00002578459,0.00002270076,0.0000191114,0.00005825678,0.00001194027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007571362,0.0003793037,0.09291858,0.0007682489,0.0003624526,0.0009667203,0.0007323468,0.2225345,0.3478386,0.001144871,0.005847069,0.3257502],"study_design_scores_gemma":[0.00001682159,0.00009831662,0.1988413,0.0000351657,0.00006070562,0.0002843272,0.0003064235,0.7706004,0.02689739,0.0002441411,0.002553935,0.0000609991],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.919716,0.0003743563,0.0696338,0.00004903991,0.00002872857,0.0001200112,0.004786711,0.001650312,0.003640958],"genre_scores_gemma":[0.9503351,0.0001994534,0.04590645,0.00001540359,0.000005897532,0.00006010482,0.002633616,0.000109576,0.0007344246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01214679,"threshold_uncertainty_score":0.02415222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0170083160793281,"score_gpt":0.2106287041063083,"score_spread":0.1936203880269802,"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."}}