{"id":"W4406175061","doi":"10.1016/j.forpol.2024.103397","title":"Economic gain of genetically-selected coastal Douglas-fir: Timber, log and carbon value at varying planting densities","year":2025,"lang":"en","type":"article","venue":"Forest Policy and Economics","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia; Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Douglas fir; Value (mathematics); Carbon sequestration; Sowing; Economics; Carbon fibers; Agricultural economics; Natural resource economics; Forestry; Environmental science; Econometrics; Mathematics; Statistics; Geography; Ecology; Biology; Agronomy; Carbon dioxide","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":[0.0006372772,0.0002224299,0.000243482,0.0001387616,0.0001863494,0.0005533732,0.0004333621,0.0002601564,0.00119306],"category_scores_gemma":[0.001016167,0.0001380902,0.000239238,0.0001893645,0.0002836421,0.0002902212,0.0002194075,0.00031889,0.00008549948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002159182,"about_ca_system_score_gemma":0.0006065646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0248067,"about_ca_topic_score_gemma":0.06769715,"domain_scores_codex":[0.9998717,0.00003024378,0.000006534715,0.00002625644,0.00002645528,0.00003870991],"domain_scores_gemma":[0.9995133,0.0002807479,0.0000558862,0.00003667261,0.00005186296,0.00006158068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.002169843,0.0006613114,0.1648331,0.00007237763,0.0001157708,0.0004310211,0.0001319732,0.773133,0.04224783,0.001823017,0.0003005035,0.01408023],"study_design_scores_gemma":[0.0002030474,0.00432006,0.3452182,0.00002105054,0.0001797929,0.0001707046,0.0005375873,0.6255485,0.02122552,0.001491814,0.001006749,0.00007709522],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994367,0.000004389216,0.0001663628,0.000004251132,4.868203e-7,0.000003240741,0.00004623205,0.000002400234,0.000336005],"genre_scores_gemma":[0.9992313,0.00000810346,0.0003311794,0.000003700526,1.981948e-7,0.000005327624,0.0000931289,0.000001531409,0.0003254196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0248067,"threshold_uncertainty_score":0.04932463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00574342987224149,"score_gpt":0.2073546895793102,"score_spread":0.2016112597070688,"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."}}