{"id":"W2170823297","doi":"10.1017/s0021859612000913","title":"Projecting annual air temperature changes to 2025 and beyond: implications for vegetable production worldwide","year":2012,"lang":"en","type":"article","venue":"The Journal of Agricultural Science","topic":"Climate change impacts on agriculture","field":"Agricultural and Biological Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Horticultural and Herbal Science, Rural Development Administration; Kasetsart University; Rural Development Administration; International Center for Agricultural Research in the Dry Areas; McGill University","keywords":"Climate change; Context (archaeology); Agriculture; Food security; Abiotic component; Environmental science; Range (aeronautics); Investment (military); Agricultural productivity; Geography; Production (economics); Environmental protection; Ecology; Biology; Economics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001642109,0.0001636337,0.0001833064,0.0000350741,0.0009339696,0.0001134452,0.0004909126,0.00005464215,0.000007964994],"category_scores_gemma":[0.0005079111,0.00004019404,0.00005373097,0.001516068,0.0001284515,0.00103991,0.0001260519,0.0001939332,0.000003118368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009578379,"about_ca_system_score_gemma":0.00001733324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003154965,"about_ca_topic_score_gemma":0.0003588739,"domain_scores_codex":[0.9986693,0.00005528358,0.000234902,0.000178879,0.0003191876,0.0005425051],"domain_scores_gemma":[0.9984025,0.0002075835,0.0002867873,0.00006053501,0.0007382028,0.0003043523],"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":[0.0000218462,0.00004512038,0.002081076,0.000005870251,0.000006314775,4.944638e-8,0.002018318,0.00002034105,0.9810125,0.00006514839,0.009281727,0.005441754],"study_design_scores_gemma":[0.00006970709,0.0003305806,0.939364,0.00004477687,0.00003936237,0.0003398524,0.009852446,3.560134e-7,0.04279001,0.00005288537,0.006950417,0.000165645],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9139805,0.0005915695,8.856641e-7,0.08430124,0.0004089596,0.0005662225,0.00004068623,0.00002114512,0.00008879705],"genre_scores_gemma":[0.9965225,0.0001133238,0.000371485,0.0008627565,0.001703965,0.00001936263,0.000005699212,9.860941e-7,0.000399877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9382224,"threshold_uncertainty_score":0.7183433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03208576430531987,"score_gpt":0.2810095961965871,"score_spread":0.2489238318912672,"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."}}