{"id":"W3169416747","doi":"10.1016/j.scitotenv.2021.148146","title":"Biorefinery potential of sustainable municipal wastewater treatment using fast-growing willow","year":2021,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières; Collège de Maisonneuve; Espace pour la vie; Université de Montréal","funders":"Natural Environment Research Council; Natural Sciences and Engineering Research Council of Canada; Engineering and Physical Sciences Research Council; Environment and Climate Change Canada","keywords":"Biorefinery; Wastewater; Bioenergy; Chemistry; Lignin; Biomass (ecology); Pulp and paper industry; Enzymatic hydrolysis; Lignocellulosic biomass; Biofuel; Agronomy; Food science; Hydrolysis; Raw material; Biotechnology; Environmental science; Biology; Environmental engineering; Biochemistry; Organic chemistry","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":[0.0002021963,0.00008823393,0.00009580652,0.00003341713,0.0001635572,0.00001335162,0.0002164676,0.00002399432,0.00009204511],"category_scores_gemma":[0.000004685798,0.00004778668,0.00008453497,0.0001715451,0.0005008604,0.0001459383,0.0002472599,0.00005155805,0.000004607663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001730764,"about_ca_system_score_gemma":0.00002667671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006314456,"about_ca_topic_score_gemma":7.623712e-8,"domain_scores_codex":[0.9992114,0.0000247314,0.0001386356,0.0001384386,0.0002712611,0.0002155199],"domain_scores_gemma":[0.9995177,0.00000430097,0.00003816394,0.0004001914,0.000009016137,0.00003064012],"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":[0.000003492302,0.00002452866,0.000002985879,0.00001474031,0.0000101601,0.000001271742,0.000244916,0.3120976,0.6873987,0.00002997619,0.000003288969,0.0001683835],"study_design_scores_gemma":[0.0001508151,0.00003414914,0.0003846357,0.00001097985,0.00003132837,0.00001987479,0.002332903,0.03873146,0.9579766,0.00003704965,0.000225806,0.0000643793],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988473,0.0001696736,0.00002024915,0.0003451518,0.0002772046,0.0001058077,0.000002474708,0.000009716673,0.0002223982],"genre_scores_gemma":[0.9981401,0.00004789463,0.0002655073,0.000004080771,0.00002969948,0.00000161278,5.217342e-7,0.000006387835,0.001504189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2733661,"threshold_uncertainty_score":0.1948684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009250906650960618,"score_gpt":0.1875909361882611,"score_spread":0.1783400295373005,"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."}}