{"id":"W2972526417","doi":"10.34133/2019/6036453","title":"High-Throughput UAV Image-Based Method Is More Precise Than Manual Rating of Herbicide Tolerance","year":2019,"lang":"en","type":"article","venue":"Plant Phenomics","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canada First Research Excellence Fund; Saskatchewan Pulse Growers","keywords":"Normalized Difference Vegetation Index; Vegetation (pathology); Multispectral image; Artificial intelligence; Visual inspection; Mathematics; Precision agriculture; Statistics; Computer science; Agronomy; Biology; Leaf area index; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002693614,0.0002247117,0.0003288819,0.00002020879,0.00006314579,0.00003559978,0.0003285986,0.0001015814,0.0003263754],"category_scores_gemma":[0.00002770478,0.0001819515,0.0000869111,0.0001450433,0.0000939302,0.0001755229,0.000137856,0.0002002807,0.0003385906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001518733,"about_ca_system_score_gemma":0.00001579379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007134198,"about_ca_topic_score_gemma":0.00007027451,"domain_scores_codex":[0.9984725,0.00007819133,0.0003399292,0.000455015,0.0003396131,0.0003148099],"domain_scores_gemma":[0.9990399,0.0001803179,0.0002529296,0.0004366002,0.00001422187,0.00007601062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001769934,0.0001380559,0.01749076,0.00009400516,0.00003683331,0.00001830929,0.00276993,0.1357184,0.829182,0.00008925337,0.008414609,0.005870761],"study_design_scores_gemma":[0.001695903,0.0001771528,0.08249837,0.0002439831,0.00007305622,0.00006176669,0.0006073083,0.2112558,0.6970446,0.0006551943,0.004747202,0.0009396651],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897462,0.00002617165,0.005356025,0.0003652142,0.0003115761,0.0003603872,0.000128034,0.00004740863,0.00365899],"genre_scores_gemma":[0.6503129,0.000009036424,0.3482127,0.0005502718,0.00009596303,0.000001465921,0.00006352439,0.00002886596,0.0007252268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3428567,"threshold_uncertainty_score":0.7419766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00609336905526032,"score_gpt":0.2286742952442776,"score_spread":0.2225809261890173,"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."}}