{"id":"W4408972423","doi":"10.1016/j.egyr.2025.03.038","title":"Integrating dynamic pricing strategies and demand-driven supply planning in wood pellet supply chains: A stochastic optimization approach","year":2025,"lang":"en","type":"article","venue":"Energy Reports","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"École Nationale d'Administration Publique; Université du Québec à Montréal","funders":"Canada Research Chairs","keywords":"Pellet; Supply chain; Supply and demand; Business; Mathematical optimization; Computer science; Economics; Microeconomics; Materials science; Mathematics; Marketing","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001893688,0.001067108,0.001494134,0.0008171499,0.000599739,0.001863039,0.001585117,0.001748297,0.002340629],"category_scores_gemma":[0.003729755,0.001303533,0.001255801,0.001231891,0.0009504909,0.00141268,0.0008918687,0.001488231,0.0002289987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002572479,"about_ca_system_score_gemma":0.003138647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03873384,"about_ca_topic_score_gemma":0.02513221,"domain_scores_codex":[0.9989343,0.0005120367,0.00004122419,0.0001560671,0.000196562,0.0001597629],"domain_scores_gemma":[0.998121,0.001264178,0.0002692098,0.00004690785,0.0002114529,0.00008721586],"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":[0.000004127849,0.000005428182,0.00009243,0.000003858095,0.000005777101,0.00001142766,0.000004072948,0.99753,0.00003770457,0.001797868,0.00003000408,0.0004772832],"study_design_scores_gemma":[0.000001744038,0.000004016048,0.00002881809,0.000001250308,0.000002266932,0.000002167107,0.000002811493,0.9990532,0.00001850792,0.0008257529,0.00005753466,0.000001995782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05662948,0.0003030994,0.9332163,0.0006764264,0.00004855263,0.0001220887,0.0002578546,0.0001626433,0.008583483],"genre_scores_gemma":[0.9202988,0.0004657279,0.07228927,0.0001487916,0.00005204415,0.0002587281,0.0002527277,0.00006707502,0.00616694],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03873384,"threshold_uncertainty_score":0.07701677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00456324752047142,"score_gpt":0.2096078493919022,"score_spread":0.2050446018714308,"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."}}