{"id":"W3186233651","doi":"10.1016/j.rser.2021.111503","title":"Performances of a multi-product strategy for bioethanol, lignin, and ultra-high surface area carbon from lignocellulose by PHP (phosphoric acid plus hydrogen peroxide) pretreatment platform","year":2021,"lang":"en","type":"article","venue":"Renewable and Sustainable Energy Reviews","topic":"Supercapacitor Materials and Fabrication","field":"Materials Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"National Natural Science Foundation of China","keywords":"Lignin; Biofuel; Supercapacitor; Chemistry; Phosphoric acid; Activated carbon; Biomass (ecology); Carbon fibers; Cellulose; Lignocellulosic biomass; Hydrogen peroxide; Adsorption; Specific surface area; Chemical engineering; Pulp and paper industry; Nuclear chemistry; Materials science; Organic chemistry; Capacitance; Electrode; Waste management; Catalysis; Composite material; Agronomy; Composite number","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":[0.0001264717,0.0004949527,0.0003241656,0.0002789526,0.0002113964,0.0003429217,0.0005039799,0.0004913564,0.001439741],"category_scores_gemma":[0.0001252454,0.0001844791,0.0003716463,0.0002734009,0.0001358948,0.0003544389,0.0002842658,0.0005509512,0.000424408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002873944,"about_ca_system_score_gemma":0.0003045959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001613228,"about_ca_topic_score_gemma":0.003419571,"domain_scores_codex":[0.9998286,0.000007460607,0.000009117994,0.00003481292,0.00007331494,0.00004665727],"domain_scores_gemma":[0.9999443,0.00000617922,0.000008674779,0.000005473755,0.00002199919,0.00001321452],"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":[0.0001551547,0.00005194399,0.00008436675,0.00004601421,0.000007059617,0.00004964137,0.00001503767,0.0002536656,0.9968527,0.00004803777,0.00007417479,0.002362153],"study_design_scores_gemma":[0.000005459463,0.0001856016,0.0005161449,0.000001358092,0.000008438607,0.00001672518,0.00001229418,0.0009233596,0.9980243,0.000008913481,0.0002926789,0.000004654011],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967645,0.0004189523,0.001218016,0.00003852898,0.00002712112,0.00001599271,0.0001819972,0.00007364139,0.001261335],"genre_scores_gemma":[0.9964908,0.0003111328,0.001327916,0.00001635387,0.000003398013,0.00001475636,0.0002494735,0.00001426281,0.001571826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001613228,"threshold_uncertainty_score":0.004816473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278910354197518,"score_gpt":0.2424448807495943,"score_spread":0.2145538453298425,"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."}}