{"id":"W2971545660","doi":"10.1088/1755-1315/323/1/012142","title":"Linking construction timber carbon storage with land use and forestry management practices","year":2019,"lang":"en","type":"article","venue":"IOP Conference Series Earth and Environmental Science","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of British Columbia","funders":"","keywords":"Greenhouse gas; Sustainability; Land use, land-use change and forestry; Thinning; Forestry; Carbon sequestration; Land use; Forest management; Agriculture; Wood production; Business; Environmental science; Forest product; Agroforestry; Natural resource economics; Economics; Geography; Engineering; Ecology","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":[0.0009464149,0.000359587,0.0002087979,0.001202685,0.0002161771,0.0009180589,0.0002934361,0.0003058265,0.001822985],"category_scores_gemma":[0.00186578,0.0001582215,0.0004570276,0.00152019,0.0002805018,0.0005723302,0.0003798961,0.0001654947,0.0002360307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001061757,"about_ca_system_score_gemma":0.0005774969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01782319,"about_ca_topic_score_gemma":0.0226206,"domain_scores_codex":[0.9997359,0.00009883278,0.00001867124,0.00004732092,0.00005756932,0.00004166306],"domain_scores_gemma":[0.9986235,0.00075293,0.0002293475,0.0000813439,0.0002487566,0.00006407728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004308428,0.0001929032,0.8024731,0.00010675,0.0003345583,0.0001473644,0.000173893,0.1701663,0.008087561,0.001392733,0.0002240024,0.01626993],"study_design_scores_gemma":[0.00001179646,0.0003100058,0.665713,0.0000211717,0.000102024,0.00007904774,0.0002616016,0.3238827,0.006730897,0.001801064,0.001049409,0.00003735543],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964155,0.00005245179,0.001358884,0.00002224853,0.000001648783,0.00002396298,0.0008473893,0.00001607216,0.001261772],"genre_scores_gemma":[0.9990101,0.00001389933,0.0003702372,0.000003347341,5.410976e-7,0.00001139295,0.0002902568,0.00000302622,0.0002971641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01782319,"threshold_uncertainty_score":0.0354389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009087128504220788,"score_gpt":0.2043037595720177,"score_spread":0.1952166310677969,"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."}}