{"id":"W2080849056","doi":"10.1080/01431160512331326567","title":"Usefulness and limits of MODIS GPP for estimating wheat yield","year":2005,"lang":"en","type":"article","venue":"International Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University; U.S. Department of Agriculture; National Aeronautics and Space Administration","keywords":"Yield (engineering); Moderate-resolution imaging spectroradiometer; Environmental science; Productivity; Climatology; Physical geography; Statistics; Mathematics; Geography; Satellite; Geology; Economics","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":[0.009530166,0.0004606055,0.0004758459,0.0009541316,0.0005912424,0.002594479,0.0008215166,0.0009305186,0.0002456181],"category_scores_gemma":[0.05643128,0.000443841,0.0004981694,0.001227988,0.001068891,0.002443781,0.00143956,0.0009820309,0.0001991002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009252447,"about_ca_system_score_gemma":0.0006262473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008293234,"about_ca_topic_score_gemma":0.00614172,"domain_scores_codex":[0.9960189,0.001802392,0.0003800587,0.0006321943,0.001042375,0.000123973],"domain_scores_gemma":[0.978337,0.01494557,0.001415548,0.002747405,0.002343583,0.0002108203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006591793,0.00008991673,0.6015031,0.0004570509,0.0002817195,0.0007322517,0.002847524,0.1001354,0.0137044,0.0133667,0.003220157,0.2630027],"study_design_scores_gemma":[0.0001134548,0.0002947838,0.3887624,0.0004825396,0.0003011029,0.001807804,0.002173348,0.5469334,0.01689314,0.02785065,0.01414892,0.0002384773],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9041914,0.00334133,0.07940283,0.002366908,0.00005420465,0.00004078534,0.0005787942,0.0005399247,0.009483762],"genre_scores_gemma":[0.9722804,0.0005353328,0.02654962,0.00007652052,0.00004408382,0.00003207185,0.0002621274,0.00004308633,0.0001768252],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009530166,"threshold_uncertainty_score":0.05040097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02342179229089441,"score_gpt":0.266000275147829,"score_spread":0.2425784828569346,"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."}}