{"id":"W2185820852","doi":"","title":"Remote sensing, geographic information system and modeling techniques for wheat area and production estimation.","year":2010,"lang":"en","type":"article","venue":"Journal of Farm Sciences","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Yield (engineering); Crop yield; Estimation; Agricultural engineering; Global Positioning System; Crop; Crop simulation model; Normalized Difference Vegetation Index; Environmental science; Productivity; Geography; Computer science; Climate change; Agronomy; Ecology; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001046594,0.0000732691,0.00009931083,0.0001010941,0.0002970317,0.0001581219,0.0000798098,0.00005263099,9.097257e-7],"category_scores_gemma":[0.0001500896,0.00004683515,0.00002515377,0.0001924269,0.0002344065,0.0008833996,0.00002882129,0.000129695,5.1508e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002687931,"about_ca_system_score_gemma":0.00001088696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000714697,"about_ca_topic_score_gemma":0.00004652948,"domain_scores_codex":[0.9992211,0.00001514768,0.0002554471,0.0001068181,0.0002931069,0.0001083575],"domain_scores_gemma":[0.9995468,0.0000225138,0.0002499951,0.00005859584,0.00006679959,0.00005529162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002732934,0.000009945276,0.002265226,0.0000830553,0.00001001901,0.00000182104,0.001510641,0.03092098,0.1117432,0.0001152176,0.0003622481,0.8529503],"study_design_scores_gemma":[0.00008704553,0.0001140176,0.002083245,0.0001086234,0.00001817262,0.001176221,0.0005893411,0.9897904,0.004378117,0.001163758,0.0003935959,0.0000973997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9241908,0.0000215924,0.07399135,0.0008050792,0.0002880912,0.0001703048,4.627393e-7,0.00002225275,0.0005100304],"genre_scores_gemma":[0.7545453,0.00002296903,0.2453444,0.00002594372,0.00005312217,5.412019e-8,2.291765e-7,0.000001567362,0.000006413381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9588695,"threshold_uncertainty_score":0.2284558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192717463834128,"score_gpt":0.233068519033473,"score_spread":0.2211413443951318,"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."}}