{"id":"W4311671363","doi":"10.1016/j.jenvman.2022.116866","title":"Resource allocation in a collaborative reforestation value chain: Optimisation with multi-objective models","year":2022,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reforestation; Sustainability; Process (computing); Environmental economics; Resource (disambiguation); Business; Value (mathematics); Computer science; Agroforestry; Environmental science; Ecology; Economics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003931622,0.001355718,0.003022127,0.001547418,0.001328525,0.003541179,0.002595333,0.005475223,0.00571792],"category_scores_gemma":[0.006760834,0.002086628,0.002044045,0.002103915,0.001674187,0.003522928,0.0025561,0.002384703,0.0004607385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002768804,"about_ca_system_score_gemma":0.002505447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02860049,"about_ca_topic_score_gemma":0.01644468,"domain_scores_codex":[0.9987057,0.0005542634,0.00005379049,0.0002556123,0.0001499418,0.0002806337],"domain_scores_gemma":[0.9947137,0.004129478,0.0004104178,0.0001236865,0.0003158418,0.0003068296],"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":[0.00001729332,0.00001345535,0.00009196591,0.00000871847,0.000009479743,0.00002269477,0.00000780813,0.9983959,0.00004750497,0.0006088946,0.00003560324,0.0007406118],"study_design_scores_gemma":[0.00001256442,0.00002359606,0.00006205514,0.000004071746,0.000006511499,0.000004031511,0.000009875193,0.9987186,0.00004803983,0.001033467,0.00007283279,0.000004314663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3148112,0.001070682,0.6600932,0.001193853,0.0001499231,0.0004397091,0.0004784228,0.000243508,0.02151946],"genre_scores_gemma":[0.9449869,0.0003402807,0.04538195,0.0001013052,0.00003866872,0.000295749,0.0001763633,0.00006945471,0.008609389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02860049,"threshold_uncertainty_score":0.05686802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008055765036371466,"score_gpt":0.2127217897454613,"score_spread":0.2046660247090898,"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."}}