{"id":"W2625345799","doi":"","title":"High Resolution Modelling of Crop Response to Climate Change","year":2014,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Lethbridge","funders":"","keywords":"Climate change; Environmental science; Crop; Remote sensing; Climatology; Geography; Geology; Forestry; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001092298,0.0001264271,0.0001306834,0.00002255422,0.0001736448,0.00002234154,0.0002346644,0.00005306012,0.00002302743],"category_scores_gemma":[0.00008558141,0.00009117468,0.00004123736,0.0001774805,0.0001011071,0.0002310999,0.0001909114,0.00007911627,0.0005028162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006996057,"about_ca_system_score_gemma":0.000001211796,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01186009,"about_ca_topic_score_gemma":0.001015682,"domain_scores_codex":[0.9985776,0.00008752601,0.0002707702,0.0003165399,0.0003840079,0.0003635657],"domain_scores_gemma":[0.9994311,0.0001168247,0.0001456343,0.0001496428,0.00000469582,0.0001520607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001386091,0.00008643102,0.03298566,0.00001192072,0.000002508923,0.000003759859,0.0008194417,0.7695214,0.1891857,0.00003902059,0.0002059232,0.006999712],"study_design_scores_gemma":[0.0001965214,0.0002639684,0.9683755,0.0001472958,0.00001084616,0.000004559708,0.0001325885,0.007355988,0.02005904,0.0002228105,0.002919407,0.0003114462],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993811,0.00001338854,0.00006191243,0.0008226982,0.00009916387,0.0001515439,0.000004468031,0.00003570171,0.005000176],"genre_scores_gemma":[0.993632,0.0000216287,0.005904452,0.0002286764,0.00007077277,0.00001223312,0.000002790005,0.000006450996,0.0001209796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9353899,"threshold_uncertainty_score":0.99472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02457377631710474,"score_gpt":0.2148601196356669,"score_spread":0.1902863433185622,"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."}}