{"id":"W2007209902","doi":"10.1089/ind.2007.3.112","title":"Selecting the most appropriate products for the forest biorefinery","year":2007,"lang":"en","type":"article","venue":"Industrial Biotechnology","topic":"Biofuel production and bioconversion","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Natural Sciences and Engineering Research Council of Canada","funders":"National Renewable Energy Laboratory","keywords":"Biorefinery; Flexibility (engineering); Identification (biology); Product (mathematics); Forest product; Supply chain; Process (computing); Business; Risk analysis (engineering); Computer science; Engineering; Economics; Environmental science; Marketing; Forest management; Biofuel","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":[0.0008171178,0.0001451128,0.0001165505,0.0001109183,0.0002680788,0.00002916734,0.0003413451,0.0006497932,0.000006686147],"category_scores_gemma":[0.0003698408,0.00008031209,0.00004270675,0.000740067,0.0002000011,0.00004161395,0.00005959049,0.0006732499,0.00002032013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005205141,"about_ca_system_score_gemma":0.00002815702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003866037,"about_ca_topic_score_gemma":0.00002819179,"domain_scores_codex":[0.9990608,0.00001254586,0.0002302481,0.0002270384,0.00009010666,0.0003792645],"domain_scores_gemma":[0.9993655,0.0001377555,0.0000551217,0.0003731334,0.00004698047,0.00002147715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001986823,0.00004305991,0.0004392311,0.00006766644,0.000174473,0.000003394882,0.000122374,0.0005977329,0.3148504,0.00303295,0.04878342,0.6316866],"study_design_scores_gemma":[0.0004387016,0.00006132507,0.00005187592,0.000005358374,0.00002122674,0.00002157564,0.0002224546,0.001177709,0.4750633,0.0001545936,0.5226631,0.0001187944],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8373366,0.001941516,0.01949658,0.1175948,0.01534061,0.004203759,0.00003315789,0.003223502,0.0008295184],"genre_scores_gemma":[0.9973238,0.00007383306,0.0003117486,0.0001411208,0.001874591,0.00003084771,0.00000841483,0.0000265948,0.0002090406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6315678,"threshold_uncertainty_score":0.50118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03227118521528899,"score_gpt":0.2254716070527862,"score_spread":0.1932004218374972,"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."}}