{"id":"W2801656539","doi":"10.1371/journal.pone.0196392","title":"Diversification and intensification of agricultural adaptation from global to local scales","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Agricultural Innovations and Practices","field":"Agricultural and Biological Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Consortium of International Agricultural Research Centers","keywords":"Diversification (marketing strategy); Agriculture; Agricultural diversification; Adaptive capacity; Natural resource economics; Agricultural productivity; Climate change; Geography; Environmental resource management; Context (archaeology); Business; Economics; 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":[0.00006855415,0.00007067757,0.000100664,0.000005902055,0.0001264932,0.00003541397,0.00009106718,0.00005165001,0.0001074863],"category_scores_gemma":[0.00007744171,0.00002620015,0.00001580852,0.0004133359,0.00008015561,0.0002451006,0.00004092424,0.00003502635,0.00004931595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000225948,"about_ca_system_score_gemma":0.000001942134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008935055,"about_ca_topic_score_gemma":0.00119074,"domain_scores_codex":[0.9993661,0.00003221353,0.0001615013,0.000180999,0.0001733017,0.00008590437],"domain_scores_gemma":[0.999226,0.00007924281,0.0001177571,0.0000344283,0.0004927745,0.00004974888],"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":[0.00004813646,0.0002545941,0.01323996,0.000004547936,0.00004584414,7.578944e-8,0.0003223281,0.000001544883,0.9163247,0.001002273,0.0003814967,0.0683745],"study_design_scores_gemma":[0.00004537455,0.0002168433,0.9642578,0.00003056034,0.00003438837,4.593991e-7,0.002852144,0.0001348596,0.03190174,0.0002373012,0.0002028572,0.00008562209],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959065,0.00004719637,0.0001481908,0.003142034,0.0000231766,0.0001595691,0.0000824344,0.00002978627,0.0004611229],"genre_scores_gemma":[0.9973509,0.00001907533,0.002073205,0.0001190906,0.000186717,0.000007437787,0.0002028571,2.58236e-7,0.00004049943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9510179,"threshold_uncertainty_score":0.1350719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09066780926555652,"score_gpt":0.2341826597946257,"score_spread":0.1435148505290691,"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."}}