{"id":"W3201217863","doi":"10.1002/wfp2.12030","title":"Global distribution of forest classes and leaf biomass for use as alternative foods to minimize malnutrition","year":2021,"lang":"en","type":"article","venue":"World Food Policy","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"John and Melinda Thompson Endowment Fund in Vision Neurosciences","keywords":"Biomass (ecology); Malnutrition; Distribution (mathematics); Prioritization; Agroforestry; Geography; Biology; Toxicology; Business; Ecology; Mathematics; Economic growth; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002690607,0.0001864239,0.0001185608,0.0014825,0.0001609118,0.000375456,0.0001554891,0.0001092459,0.00213936],"category_scores_gemma":[0.0004767808,0.00006469571,0.0001900439,0.00127832,0.0001584954,0.0002881764,0.0002834052,0.0001069135,0.000271775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000201059,"about_ca_system_score_gemma":0.0001472268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006530591,"about_ca_topic_score_gemma":0.02040383,"domain_scores_codex":[0.9999146,0.00002327691,0.000005158251,0.00002389992,0.00001479071,0.00001824928],"domain_scores_gemma":[0.9996225,0.0000632867,0.0001807564,0.00002416432,0.00007409232,0.00003513036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001383633,0.00001953394,0.9633043,0.00006367707,0.00006896712,0.00005234148,0.0001722606,0.0009363673,0.008654372,0.0002462388,0.0002765689,0.02606712],"study_design_scores_gemma":[0.000001680613,0.00003068587,0.99764,0.00001426335,0.00001808289,0.00006398305,0.0002984458,0.0006708155,0.0004922805,0.0001687262,0.0005987472,0.000002301691],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926972,0.000452523,0.001528671,0.00006811044,0.000002493691,0.00001938489,0.002256075,0.00002461192,0.002950957],"genre_scores_gemma":[0.9977595,0.0001565983,0.001228901,0.00001158134,0.00000193909,0.000007996691,0.0006020053,0.000004330321,0.0002272078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006530591,"threshold_uncertainty_score":0.01298517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663647631244352,"score_gpt":0.2770683481862043,"score_spread":0.2604318718737608,"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."}}