{"id":"W1934912008","doi":"10.4141/cjps2011-266","title":"Evaluation of the APSIM-Wheat model in terms of different cultivars, management regimes and environmental conditions","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Plant Science","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Bijzonder Onderzoeksfonds UGent; National Natural Science Foundation of China; National Science Foundation","keywords":"Sowing; Phenology; Cultivar; Yield (engineering); Agronomy; Crop simulation model; Mathematics; Crop; Biomass (ecology); Leaf area index; Crop yield; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007658689,0.00005882893,0.0000971913,0.00004427311,0.0001001,0.00001547194,0.0002267674,0.0000234489,0.00005250864],"category_scores_gemma":[0.00003995083,0.00001838892,0.00002925717,0.0001791742,0.0002553594,0.0002097859,0.00002548842,0.00006211579,2.352656e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001476867,"about_ca_system_score_gemma":0.00002834912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003056007,"about_ca_topic_score_gemma":0.006385569,"domain_scores_codex":[0.9990788,0.00004750391,0.0001754318,0.0000664039,0.0004410255,0.0001908376],"domain_scores_gemma":[0.9995272,0.00002774029,0.0001674851,0.00003446698,0.00002881212,0.0002143123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000008400591,0.0001179808,0.335105,0.00001303783,0.00001571064,0.000003449359,0.002139905,0.0004437294,0.6545212,0.0008706602,0.0008196975,0.005941212],"study_design_scores_gemma":[0.0001323511,0.00003516511,0.9919354,0.00008975492,0.00003025766,0.00004426166,0.00137413,0.0008825205,0.004948851,0.0004212472,0.00005545889,0.00005056354],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985604,0.0001310609,2.957883e-7,0.0003615677,0.0000815971,0.0001365588,0.0003582678,4.985533e-7,0.0003697812],"genre_scores_gemma":[0.9998574,0.00004855122,0.00001280061,0.00003230645,0.00002035362,0.000001311,0.000008588119,2.597919e-7,0.00001844235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6568304,"threshold_uncertainty_score":0.3563297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04423475714092185,"score_gpt":0.2396645672276875,"score_spread":0.1954298100867657,"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."}}