{"id":"W4318477272","doi":"","title":"A WOOD ALLOCATION DECISION PROCESS FOR MAXIMAZING VALUE CREATION FROM PUBLIC FORESTS","year":2014,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Process (computing); Value (mathematics); Computer science; Machine learning","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":[0.007253943,0.0008549563,0.002133632,0.001243536,0.001100359,0.00331751,0.002529286,0.00413601,0.01959743],"category_scores_gemma":[0.01311775,0.0008525004,0.001339025,0.001436567,0.001653273,0.003915701,0.002717604,0.003228884,0.001067615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003323549,"about_ca_system_score_gemma":0.003822126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007378227,"about_ca_topic_score_gemma":0.006148352,"domain_scores_codex":[0.9977088,0.001126447,0.000112838,0.0004240397,0.0002811646,0.0003466391],"domain_scores_gemma":[0.9921549,0.006532164,0.0003015057,0.0002238898,0.0004262899,0.0003613778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006896521,0.0002389635,0.001271727,0.0001570363,0.0000852361,0.0001476603,0.0003295489,0.8292793,0.001375686,0.1091663,0.002749205,0.05450956],"study_design_scores_gemma":[0.00005969347,0.000054498,0.0001978363,0.00002008915,0.00002147623,0.00001346675,0.00005820312,0.9552083,0.0005483042,0.04304418,0.000761375,0.0000125668],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.08549561,0.0002815742,0.8954324,0.002084462,0.00009363381,0.0004646768,0.0004799945,0.0002911994,0.01537642],"genre_scores_gemma":[0.7794427,0.0002740437,0.2071963,0.0002053716,0.000111631,0.0005954958,0.0004085413,0.00009187284,0.01167428],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01959743,"threshold_uncertainty_score":0.06555998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01875847064309921,"score_gpt":0.2556994359659817,"score_spread":0.2369409653228824,"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."}}