{"id":"W2555683065","doi":"10.1139/cjfr-2016-0299","title":"Strategic planning in a forest supply chain: a multigoal and multiproduct approach","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consejo Nacional de Investigaciones Científicas y Técnicas","keywords":"Maximization; Sustainability; Minification; Work (physics); Supply chain; Schedule; Production (economics); Yield (engineering); Forest management; Operations research; Computer science; Environmental economics; Business; Economics; Environmental science; Mathematics; Agroforestry; Ecology; Microeconomics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001892805,0.001378482,0.001233445,0.00174313,0.000894161,0.002489479,0.001780866,0.002000547,0.004489047],"category_scores_gemma":[0.002444005,0.000992008,0.001519565,0.001936257,0.002078125,0.00203043,0.001650456,0.001613763,0.0003392761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003479262,"about_ca_system_score_gemma":0.003011328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01233675,"about_ca_topic_score_gemma":0.01302624,"domain_scores_codex":[0.9988058,0.0006932946,0.00003667427,0.0001461577,0.0001870294,0.0001310807],"domain_scores_gemma":[0.9987103,0.0009047888,0.0001128439,0.00003751025,0.0001127677,0.0001218445],"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":[0.00002637375,0.00005262759,0.0003025368,0.00008070438,0.00004158463,0.0001379061,0.00009290948,0.9393085,0.0002669303,0.05385068,0.0002958114,0.005543463],"study_design_scores_gemma":[0.00001562411,0.00004730379,0.0001254321,0.00002726511,0.00001944024,0.00002621202,0.00007379222,0.9434266,0.0001314247,0.05499821,0.001096702,0.00001197923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0259381,0.0006037732,0.9566209,0.0008518441,0.00003768849,0.0001511742,0.0001228293,0.00006715267,0.01560644],"genre_scores_gemma":[0.5612892,0.001363281,0.4264886,0.0002168381,0.00006455347,0.0005139876,0.0001760381,0.00007959751,0.009807965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9876633,"threshold_uncertainty_score":0.02524388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07447308180755687,"score_gpt":0.3018994920027888,"score_spread":0.2274264101952319,"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."}}