{"id":"W3213584587","doi":"10.1002/bbb.2312","title":"Climate change affects cell‐wall structure and hydrolytic performance of a perennial grass as an energy crop","year":2021,"lang":"en","type":"article","venue":"Biofuels Bioproducts and Biorefining","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Cellulose; Panicum virgatum; Panicum; Biomass (ecology); Crystallinity; Forage; Agronomy; Bioenergy; Perennial plant; Climate change; Global warming; Environmental science; Hemicellulose; Xylan; Cell wall; Cellulosic ethanol; Starch; Hydrolysis; Biofuel; Chemistry; Food science; Biology; Biotechnology; Ecology; Biochemistry","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":[0.0001244048,0.0002789576,0.000284338,0.0001285888,0.0001457293,0.00007247255,0.00009194602,0.0001997975,0.00004279024],"category_scores_gemma":[0.000009751469,0.000236281,0.00003525328,0.0002889211,0.0001397704,0.0002822287,0.0001020737,0.0001553765,0.000003232893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001593275,"about_ca_system_score_gemma":0.00001915534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004611585,"about_ca_topic_score_gemma":0.00000975109,"domain_scores_codex":[0.9986893,0.00003179025,0.000211603,0.000541904,0.0001628668,0.0003625662],"domain_scores_gemma":[0.9993962,0.000008082547,0.00007139226,0.0002993229,0.00007367891,0.0001513119],"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":[0.00006125506,0.00004993168,0.005683827,0.001343922,0.00002490763,0.00001575402,0.0005105793,0.000005354203,0.9079265,0.0001835502,0.0000333118,0.08416112],"study_design_scores_gemma":[0.0007081758,0.0004338566,0.00971092,0.0001298478,0.00005125557,0.0001322778,0.0001416696,0.00313419,0.9771233,0.00005573391,0.007890073,0.0004887623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925339,0.006191481,0.000001177555,0.0002743416,0.0005232413,0.00009341993,0.00003962103,0.0001256789,0.0002171669],"genre_scores_gemma":[0.9923697,0.006457596,0.0004594343,0.0001437465,0.0004062705,0.000004359481,0.00005601675,0.0000342339,0.00006865345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08367235,"threshold_uncertainty_score":0.963526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153665721703076,"score_gpt":0.1995707842360946,"score_spread":0.1880341270190638,"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."}}