{"id":"W2731487300","doi":"10.15017/1809681","title":"Modeling and Optimization of Biomass Supply Chain for Energy, Chemicals and Materials Productions","year":2016,"lang":"en","type":"article","venue":"Kyushu University Institutional Repository (QIR) (Kyushu University)","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Supply chain; Biomass (ecology); Environmental science; Process engineering; Pulp and paper industry; Business; Engineering; Agronomy; Biology","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":[0.00073018,0.001190591,0.001171171,0.0008253708,0.0008307461,0.002307341,0.001221324,0.002535753,0.008520482],"category_scores_gemma":[0.001508283,0.0008516536,0.001575644,0.00112972,0.0007872477,0.001005228,0.001151046,0.001254766,0.0008127448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002088975,"about_ca_system_score_gemma":0.002400521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03215522,"about_ca_topic_score_gemma":0.01700202,"domain_scores_codex":[0.9996105,0.0001060487,0.00001669844,0.00008001879,0.0000708919,0.0001159009],"domain_scores_gemma":[0.9993854,0.00034299,0.00007151007,0.00001857242,0.0001294155,0.0000522054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001533992,0.00001245088,0.0003040021,0.00002529897,0.000008068637,0.00004736786,0.00001197287,0.9959966,0.0001734397,0.002147287,0.0002170545,0.001041124],"study_design_scores_gemma":[0.000004984251,0.00001107148,0.00009193894,0.000007325423,0.000004882977,0.000005959885,0.00001870382,0.9980499,0.00007000064,0.001143119,0.0005891304,0.000002989528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.25097,0.00345572,0.6215894,0.002603664,0.0004439073,0.0004388482,0.003249444,0.0008387511,0.1164103],"genre_scores_gemma":[0.9303671,0.001538966,0.03086078,0.0001376442,0.00004840278,0.0004242414,0.0009181984,0.0001256108,0.03557907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03215522,"threshold_uncertainty_score":0.06393611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007202393116048883,"score_gpt":0.1583046591746415,"score_spread":0.1511022660585926,"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."}}