{"id":"W3183894457","doi":"10.1016/j.agee.2021.107555","title":"Climate change mitigation and adaptation in agriculture: Why agroforestry should be part of the solution","year":2021,"lang":"en","type":"article","venue":"Agriculture Ecosystems & Environment","topic":"Agroforestry and silvopastoral systems","field":"Agricultural and Biological Sciences","cited_by":86,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Agroforestry; Agriculture; Adaptation (eye); Climate change; Climate change adaptation; Agroecosystem; Climate change mitigation; Environmental science; Geography; Ecology; Biology","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":[0.0003023772,0.0002283313,0.0002833217,0.00000785364,0.000225636,0.00004116818,0.0001587508,0.0002579597,0.00006345624],"category_scores_gemma":[0.00001898939,0.00007727295,0.0001211807,0.000296878,0.00005116674,0.0002335481,0.0001313849,0.0001883194,0.000008853397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009244969,"about_ca_system_score_gemma":0.000004221423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006032847,"about_ca_topic_score_gemma":0.008074392,"domain_scores_codex":[0.9980503,0.000287643,0.0005174513,0.0004158329,0.0003973307,0.0003314169],"domain_scores_gemma":[0.9993724,0.00006253432,0.0003347003,0.0001070247,0.00003331434,0.00008999916],"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":[0.00002019166,0.0002591969,0.1096433,0.0001203597,0.00002818164,0.00001461989,0.0007973467,0.0001224057,0.8786579,0.0009646653,0.004100241,0.005271533],"study_design_scores_gemma":[0.0003571455,0.0001695039,0.8764071,0.0004628656,0.00005166365,0.0000862965,0.003129009,0.0003610449,0.03893881,0.00009398134,0.07953383,0.0004086729],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935855,0.001262435,0.000005113353,0.003842788,0.0003329067,0.0006479999,0.0001178113,0.00002264016,0.0001827982],"genre_scores_gemma":[0.9981826,0.0004686035,0.00002499216,0.0002179593,0.0005130573,0.0001490051,0.0002918761,0.000001696085,0.0001502358],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8397191,"threshold_uncertainty_score":0.45057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03428687348975877,"score_gpt":0.1929664538175012,"score_spread":0.1586795803277424,"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."}}