{"id":"W2069209283","doi":"10.5589/m11-046","title":"Near-infrared imagery from unmanned aerial systems and satellites can be used to specify fertilizer application rates in tree crops","year":2011,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orchard; Remote sensing; Canopy; Environmental science; Multispectral image; Fertilizer; Precision agriculture; Leaf area index; Vegetation (pathology); Tree canopy; Geography; Agronomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000191907,0.0001647751,0.0001463344,0.0006117253,0.0001295839,0.0001815685,0.0001155813,0.0001106174,0.001102668],"category_scores_gemma":[0.0003486584,0.0001047186,0.00009660814,0.0005067629,0.00007562422,0.000189081,0.00009071887,0.00008470855,0.0002544825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002469916,"about_ca_system_score_gemma":0.000120808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006065442,"about_ca_topic_score_gemma":0.03288647,"domain_scores_codex":[0.9999208,0.00001257131,0.000004799509,0.00001715287,0.0000377131,0.000006971646],"domain_scores_gemma":[0.9998453,0.00004316839,0.00004331545,0.00001752016,0.00003864983,0.00001216666],"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":[0.0006187005,0.000201934,0.3300704,0.0002863095,0.00006686861,0.000303164,0.0005322216,0.007544209,0.4307711,0.0003276966,0.002921923,0.2263556],"study_design_scores_gemma":[0.00001680229,0.0001347071,0.9503194,0.00001583817,0.0000345246,0.000156484,0.0002044513,0.01041783,0.03528732,0.0002162466,0.003175033,0.00002145366],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9745792,0.0002577484,0.01499435,0.00002516089,0.000009836095,0.00008604042,0.001995036,0.0005059601,0.0075466],"genre_scores_gemma":[0.9554136,0.0002191592,0.04090575,0.000030264,0.000003289015,0.0000585138,0.001519634,0.00005967683,0.001790062],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006065442,"threshold_uncertainty_score":0.01206023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02221923421958899,"score_gpt":0.2131307067329115,"score_spread":0.1909114725133225,"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."}}