{"id":"W4312366441","doi":"10.2139/ssrn.4297289","title":"Carbon Balance of China-Made Wood Products Assessed Using a Trade-Linked Approach","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Forest Research Institute; Ministry of Energy, Northern Development and Mines","funders":"","keywords":"Balance (ability); China; Balance of trade; Carbon fibers; Environmental science; Business; Natural resource economics; Economics; Pulp and paper industry; International trade; Engineering; Geography; Materials science; Composite material; Medicine; Physical medicine and rehabilitation","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":[0.0005433725,0.0004989355,0.0002814981,0.002628272,0.0003772315,0.000844605,0.0004943857,0.0006337016,0.001431921],"category_scores_gemma":[0.0004698983,0.0002209885,0.001236533,0.003074157,0.000374186,0.0009217317,0.0004281703,0.0002964329,0.0001386267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001788766,"about_ca_system_score_gemma":0.0008035953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03270328,"about_ca_topic_score_gemma":0.04093932,"domain_scores_codex":[0.9998055,0.00003253802,0.000009835685,0.00005467718,0.00006955877,0.00002776968],"domain_scores_gemma":[0.9998149,0.00004695454,0.00003314959,0.00001912654,0.00007081172,0.0000150904],"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":[0.001414938,0.0006611667,0.3681759,0.0005535051,0.001424356,0.001450769,0.000253022,0.5053005,0.0575752,0.01169784,0.0009160264,0.05057684],"study_design_scores_gemma":[0.00004677394,0.0003763615,0.3847985,0.00004128298,0.0005232831,0.0001332903,0.0003987455,0.5916222,0.0163155,0.003076125,0.002596051,0.00007187091],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948217,0.0001672456,0.001617035,0.00002427454,0.000007928878,0.0000221452,0.0006789737,0.00001449253,0.002646145],"genre_scores_gemma":[0.9981291,0.00009271874,0.0006366058,0.000006525616,0.000003476209,0.00001654596,0.0004742066,0.000005387863,0.0006355191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03270328,"threshold_uncertainty_score":0.06502587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008593031159557386,"score_gpt":0.2244901082868087,"score_spread":0.2158970771272513,"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."}}