{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001022263,0.0001346063,0.0001911611,0.0000480444,0.00006188516,0.00005002412,0.0001100506,0.00004579266,0.00002578684],"category_scores_gemma":[0.0003094499,0.0001388914,0.00006735169,0.0006684039,0.00007854288,0.0002051639,0.0001514149,0.00003134823,0.00002714307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003346703,"about_ca_system_score_gemma":0.00002871937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003372696,"about_ca_topic_score_gemma":0.01041617,"domain_scores_codex":[0.998962,0.00006895359,0.000211253,0.0003080128,0.0001832929,0.0002664563],"domain_scores_gemma":[0.9993665,0.0001687449,0.0000936515,0.0002067093,0.00002639861,0.0001380473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008306389,0.000972244,0.8637646,0.0006307081,0.0002919407,0.0000309062,0.0007104872,0.0002708927,0.02463103,0.04598815,0.03506758,0.02681077],"study_design_scores_gemma":[0.002367786,0.001251281,0.8638957,0.0001888542,0.00006211123,0.00005489372,0.0001070237,0.001549867,0.05450329,0.008207674,0.06733478,0.0004767596],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928344,0.0000633765,0.002592372,0.001934412,0.0001359821,0.0005080894,0.001041604,0.00002525507,0.0008644676],"genre_scores_gemma":[0.9973656,0.0000079295,0.001860903,0.0002014227,0.0001257343,0.00007712076,0.0001021404,0.00001137846,0.000247779],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03778047,"threshold_uncertainty_score":0.5812466,"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."}}