{"id":"W2003704666","doi":"10.1109/tgrs.2014.2372897","title":"Dynamical Approach for Real-Time Monitoring of Agricultural Crops","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency; Generalitat Valenciana; Ministerio de Economía y Competitividad; University of Regina","keywords":"Agriculture; Remote sensing; Computer science; Environmental science; Agricultural engineering; Geology; Engineering; Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0002149464,0.0004029376,0.0003207545,0.0005418623,0.0001699926,0.0005209848,0.0004065396,0.0004456322,0.0009349648],"category_scores_gemma":[0.0005538656,0.0001847224,0.0005190525,0.0003907834,0.000271902,0.0005850657,0.000394797,0.0004624371,0.0002094425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003067694,"about_ca_system_score_gemma":0.0002616793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00220163,"about_ca_topic_score_gemma":0.002132434,"domain_scores_codex":[0.9998628,0.00003351632,0.000007108113,0.00005717477,0.00003022909,0.000009084905],"domain_scores_gemma":[0.9998674,0.0000626538,0.00002752461,0.0000147908,0.00002118877,0.000006349397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006723436,0.00008119624,0.004574612,0.0003359471,0.0002423228,0.0003143009,0.0001870357,0.7296037,0.05480514,0.07390317,0.001263655,0.1346216],"study_design_scores_gemma":[0.000004552665,0.00003164743,0.001541706,0.000008890281,0.00001701349,0.00005327514,0.0000190932,0.9853216,0.001355558,0.008393498,0.003238771,0.00001434755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007539191,0.0004712356,0.99059,0.00007822293,0.00003670545,0.00001189825,0.00006775708,0.00008601109,0.001118997],"genre_scores_gemma":[0.6763375,0.00174836,0.3168971,0.0001211556,0.0002309783,0.000173821,0.000466123,0.00005789595,0.003967023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00220163,"threshold_uncertainty_score":0.004377604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008215547451161608,"score_gpt":0.2146584127954174,"score_spread":0.2064428653442558,"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."}}