{"id":"W4406736979","doi":"10.1021/acssusresmgt.4c00263","title":"Carbon Footprint of Biochar from Forest Harvest Residues as a Substitute for Coal during Steel Production","year":2025,"lang":"en","type":"article","venue":"ACS Sustainable Resource Management","topic":"Coal and Its By-products","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Forest Research Institute","funders":"","keywords":"Biochar; Environmental science; Coal; Carbon footprint; Production (economics); Charcoal; Carbon fibers; Waste management; Environmental protection; Pulp and paper industry; Agroforestry; Greenhouse gas; Pyrolysis; Chemistry; Materials science; Geology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003714504,0.0001962122,0.0002403693,0.0002860476,0.0002685135,0.00008926877,0.0003320476,0.00005743442,0.00002816334],"category_scores_gemma":[0.0001504194,0.0001799301,0.00006008838,0.0004756867,0.00009370035,0.000093643,0.0001439846,0.00009409522,0.000008163121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003645726,"about_ca_system_score_gemma":0.00005478243,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01066928,"about_ca_topic_score_gemma":0.001723051,"domain_scores_codex":[0.9982845,0.00004857779,0.0003204287,0.0005687263,0.0002703278,0.0005074773],"domain_scores_gemma":[0.9991199,0.00005408186,0.0001244481,0.0004988557,0.0001392265,0.00006353042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006702986,0.0006414588,0.6294176,0.01834098,0.001955318,0.0006317839,0.003192004,0.1402327,0.005670334,0.07559172,0.006211213,0.1114119],"study_design_scores_gemma":[0.001044516,0.0002264766,0.7296565,0.0002137801,0.0001885965,0.000002361298,0.01020855,0.0002291732,0.04569812,0.007393943,0.2047604,0.0003775537],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9721762,0.001330109,0.00003442413,0.00154758,0.0001963968,0.001315027,0.00001589281,0.00006868143,0.02331572],"genre_scores_gemma":[0.9394495,0.00009262475,0.000246216,0.00003798446,0.0001571552,0.00002584967,0.0001161836,0.000007094041,0.05986733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1985492,"threshold_uncertainty_score":0.9959188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007569407561012849,"score_gpt":0.2007990866398352,"score_spread":0.1932296790788223,"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."}}