{"id":"W2152306358","doi":"10.1287/inte.30.6.32.11625","title":"The Québec Ministry of Natural Resources Uses Linear Programming to Understand the Wood-Fiber Market","year":2000,"lang":"en","type":"article","venue":"INFORMS Journal on Applied Analytics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec); Université Laval","funders":"","keywords":"Christian ministry; Government (linguistics); Negotiation; Linear programming; Natural resource; Industrial organization; Fiber; Yield (engineering); Business; Computer science; Environmental economics; Economics; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001463401,0.0008732649,0.0004213385,0.00133438,0.001925415,0.003366664,0.000893986,0.0008830252,0.008158478],"category_scores_gemma":[0.002127273,0.0004944856,0.0005970013,0.002220933,0.001101131,0.001418201,0.0004923283,0.001292747,0.0007200924],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02879123,"about_ca_system_score_gemma":0.02578646,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.939199,"about_ca_topic_score_gemma":0.9539286,"domain_scores_codex":[0.9993338,0.0002446403,0.00001983772,0.00009115686,0.0001877167,0.0001227678],"domain_scores_gemma":[0.9988372,0.0006815077,0.00009517036,0.00004437108,0.0002902536,0.00005151909],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004451854,0.00008660882,0.005575342,0.0001610823,0.00004280923,0.0001625206,0.0003320443,0.4226202,0.000647774,0.4418517,0.0500589,0.07841668],"study_design_scores_gemma":[0.00004434504,0.00004026007,0.004267975,0.0001530736,0.00002272396,0.00003586687,0.000486473,0.7488171,0.000886664,0.07476997,0.1704057,0.00006981473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06634326,0.006939339,0.5451721,0.0315416,0.0003207207,0.0006301797,0.01814112,0.001759159,0.3291525],"genre_scores_gemma":[0.6246296,0.006955412,0.2583367,0.002000925,0.0001272194,0.0005373736,0.004835863,0.0003160428,0.1022608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9712088,"threshold_uncertainty_score":0.2088959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01032985194353745,"score_gpt":0.2361617390863519,"score_spread":0.2258318871428144,"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."}}