{"id":"W4403561873","doi":"10.1007/978-3-031-56056-9_17","title":"Forecasting Crop Yield Under Climate Change Using Crop Growth Models in China: A Review","year":2024,"lang":"en","type":"review","venue":"Environmental science and engineering","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Crop; Yield (engineering); Climate change; Environmental science; China; Agroforestry; Agricultural engineering; Climatology; Geography; Forestry; Ecology; Biology; Engineering; Geology","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":[0.0006055241,0.0004624001,0.0007453671,0.00007444594,0.000187698,0.0001854549,0.0003601812,0.0001643985,0.00006307859],"category_scores_gemma":[0.00004001267,0.0001783236,0.0001513405,0.001100569,0.0001151663,0.000617567,0.000508468,0.000409856,0.00001703209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004201748,"about_ca_system_score_gemma":0.000009725851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001215447,"about_ca_topic_score_gemma":0.0000323721,"domain_scores_codex":[0.9977617,0.00001895526,0.0003961532,0.0006647202,0.00042337,0.0007350513],"domain_scores_gemma":[0.9995472,0.00005061855,0.0001136308,0.0000761193,0.000005750673,0.0002066346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000001742237,0.00008456273,0.00002758405,0.02544731,0.00002648801,0.0001186615,0.0003119321,0.0001470908,0.004309944,0.00009335539,0.0000904498,0.9693409],"study_design_scores_gemma":[0.000342027,0.0005748757,0.004416228,0.6534771,0.002288423,0.002957409,0.0007742763,0.07240448,0.00006583217,0.0002370673,0.2548977,0.007564676],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01601035,0.9827582,8.211208e-7,0.0001286793,0.0001614771,0.0006873091,0.0001167075,0.00005444479,0.00008198727],"genre_scores_gemma":[0.007324453,0.9921582,0.00005047154,0.0001169014,0.0002295742,0.00006856368,0.00003686049,0.000006955178,0.00000802664],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9617762,"threshold_uncertainty_score":0.7271825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.135504950649677,"score_gpt":0.2736658783606191,"score_spread":0.138160927710942,"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."}}