{"id":"W4401650471","doi":"10.5376/jeb.2024.15.0014","title":"Optimizing Cassava for Bioenergy: Genetic Foundations and Biochemical Mechanisms of Biomass Conversion","year":2024,"lang":"en","type":"article","venue":"Journal of Energy Bioscience","topic":"Cassava research and cyanide","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioenergy; Biomass (ecology); Biotechnology; Biochemical engineering; Agroforestry; Biofuel; Environmental science; Biology; Engineering; Agronomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003171098,0.0000763818,0.0001294357,0.0000612087,0.0001103319,0.00009627804,0.0002150245,0.00005511321,0.00003893281],"category_scores_gemma":[0.00009809153,0.00003038143,0.0001055353,0.0004288997,0.0001678493,0.0001616688,0.0000655719,0.00005315659,5.006067e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002764637,"about_ca_system_score_gemma":0.00004962362,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001001017,"about_ca_topic_score_gemma":0.00003694536,"domain_scores_codex":[0.9991084,0.0000265399,0.0002440642,0.0001626705,0.0002693307,0.0001889853],"domain_scores_gemma":[0.9993309,0.0002401853,0.0001015799,0.00003064364,0.0001551924,0.0001415304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001873549,0.00002199672,0.000033203,0.00001275815,0.000008658736,0.000009028775,0.00001024622,0.000004542677,0.9879577,0.003749539,0.0003477263,0.007825821],"study_design_scores_gemma":[0.0001550415,0.0008612723,0.001141291,0.0000969801,0.00002256845,0.0001699279,0.0001814802,0.003762092,0.9770371,0.005090319,0.01135712,0.0001248535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9839449,0.001602356,0.01209843,0.001875682,0.000319123,0.00004679333,0.00003103854,0.00001160377,0.00007007135],"genre_scores_gemma":[0.9949946,0.0003284925,0.004442597,0.0000505731,0.0001099403,0.000001871846,0.000003364609,8.531797e-7,0.00006773265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01104968,"threshold_uncertainty_score":0.1238919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02681482800374984,"score_gpt":0.263277544235332,"score_spread":0.2364627162315822,"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."}}