{"id":"W1990365663","doi":"10.1155/2012/756242","title":"Understanding Crop Response to Climate Variability with Complex Agroecosystem Models","year":2012,"lang":"en","type":"article","venue":"International Journal of Ecology","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Australian Government; University of Lethbridge; University of Montana; National Center for Atmospheric Research; National Science Foundation","keywords":"Agroecosystem; Environmental science; Climate change; Forcing (mathematics); Sensitivity (control systems); Climate sensitivity; Agricultural productivity; Productivity; Climatology; Climate model; Ecology; Agriculture; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008544335,0.0004204185,0.0004017058,0.0003415611,0.0002881536,0.0008924344,0.0007612841,0.0007012747,0.0006939668],"category_scores_gemma":[0.005089242,0.0003737507,0.0006072558,0.0004658587,0.0003653007,0.001566426,0.0006049518,0.0007097016,0.00009102224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000952818,"about_ca_system_score_gemma":0.0006240936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02518393,"about_ca_topic_score_gemma":0.02443982,"domain_scores_codex":[0.9997686,0.00009866433,0.0000153053,0.00006916817,0.00001944571,0.00002896717],"domain_scores_gemma":[0.9983211,0.001083792,0.0002355975,0.0001939494,0.0000856903,0.00007975036],"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":[0.00002035359,0.00002780362,0.01363143,0.00001158711,0.00005819088,0.00001803541,0.00004119832,0.9822725,0.0008099818,0.0009169622,0.00008926375,0.002102644],"study_design_scores_gemma":[0.000003271382,0.000006102766,0.004329165,0.0000015055,0.000005227066,0.000003097312,0.00001047743,0.9937358,0.00009534095,0.00175461,0.00005057883,0.000004713918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951663,0.00008702976,0.0463048,0.0003375957,0.0000102159,0.00002850165,0.0003541588,0.0001302613,0.001084511],"genre_scores_gemma":[0.9931991,0.00005595777,0.006362055,0.00003153225,0.000007450746,0.00002332033,0.0001619993,0.00002035584,0.0001383317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02518393,"threshold_uncertainty_score":0.05007464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05359501448844536,"score_gpt":0.2650856134654648,"score_spread":0.2114905989770194,"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."}}