{"id":"W3093693089","doi":"10.1590/1678-992x-2019-0150","title":"Soil morphostructural characterization and coffee root distribution under agroforestry system with Hevea Brasiliensis","year":2020,"lang":"en","type":"article","venue":"Scientia Agricola","topic":"Soil Management and Crop Yield","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Hevea brasiliensis; Oxisol; Agroforestry; Natural rubber; Agronomy; Root system; Soil quality; Tillage; Coffea arabica; Environmental science; Soil water; Biology; Botany; Soil science; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001739177,0.000274602,0.000229445,0.00107456,0.000428246,0.0003741894,0.0001873717,0.0001319387,0.0006244992],"category_scores_gemma":[0.0003248974,0.0001451121,0.000201859,0.0006516603,0.0003919302,0.0002197258,0.0003066176,0.0001408793,0.00008993883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006395906,"about_ca_system_score_gemma":0.0002493171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04313804,"about_ca_topic_score_gemma":0.1668526,"domain_scores_codex":[0.9997957,0.000033983,0.00001668657,0.00006867969,0.0000422419,0.00004277947],"domain_scores_gemma":[0.9997713,0.00003356903,0.00009079489,0.00001685975,0.00004916404,0.00003820404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003133141,0.0001748594,0.8902373,0.0001276598,0.0001152233,0.0007256133,0.002992497,0.0003269484,0.08279444,0.000191903,0.00009709232,0.02190318],"study_design_scores_gemma":[0.000001397994,0.00005596551,0.9981805,0.000003987146,0.00001121387,0.00009887307,0.0006848398,0.0001605098,0.0005683529,0.00002140112,0.000209516,0.00000353019],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999285,0.00009125174,0.00006238116,0.000007195543,7.044773e-7,0.000005974299,0.00009188108,0.000002153943,0.0004534396],"genre_scores_gemma":[0.9996701,0.00004176881,0.00009920125,0.000003365967,7.15959e-7,0.000003215344,0.00007585689,8.643076e-7,0.0001048867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04313804,"threshold_uncertainty_score":0.08577389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008841154827006044,"score_gpt":0.1655487180270118,"score_spread":0.1567075632000057,"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."}}