{"id":"W4223903882","doi":"10.1590/1678-992x-2021-0142","title":"Coffee crops adaptation to climate change in agroforestry systems with rubber trees in southern Brazil","year":2022,"lang":"en","type":"article","venue":"Scientia Agricola","topic":"Coffee research and impacts","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cegep Edouard Montpetit; Université de Montréal; University of Guelph","funders":"","keywords":"Coffea arabica; Hevea brasiliensis; Climate change; Environmental science; Natural rubber; Agroforestry; Crop; Agronomy; Horticulture; Biology; Ecology","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":[0.0007807906,0.0001248662,0.0002237856,0.0005998395,0.0001455756,0.0000835571,0.0001527175,0.00003222326,0.0002451554],"category_scores_gemma":[0.00006375151,0.00009337191,0.00003101884,0.001685938,0.00004321886,0.0001460532,0.0001577408,0.0002728888,0.000111946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000263053,"about_ca_system_score_gemma":0.0001921767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003400865,"about_ca_topic_score_gemma":0.009254323,"domain_scores_codex":[0.997884,0.0001320001,0.0002123685,0.0003296939,0.0008100248,0.0006318982],"domain_scores_gemma":[0.9993248,0.00004523696,0.00005481677,0.000232449,0.00006165449,0.0002810429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002274375,0.001169549,0.9260933,0.000305555,0.00004207296,0.0007501089,0.03043587,0.004496124,0.01505896,0.0002263593,0.003973739,0.01517396],"study_design_scores_gemma":[0.002521274,0.001014324,0.9760604,0.0002465922,0.00001260344,0.00006601493,0.0115702,0.005287523,0.00007857483,0.000007340606,0.002954687,0.000180495],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958895,0.0002810941,0.00001853781,0.001045452,0.0001900604,0.001272211,0.00006763063,0.00003245559,0.001202997],"genre_scores_gemma":[0.9983475,0.000009904928,0.00005532812,0.0002396414,0.00008441646,0.0003358583,0.00004494736,0.00001779391,0.0008645986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04996705,"threshold_uncertainty_score":0.5164129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03109593846893744,"score_gpt":0.2991766828008452,"score_spread":0.2680807443319078,"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."}}