{"id":"W4414483438","doi":"10.1111/gcbb.70083","title":"Maximizing Biochar Climate Change Mitigation Impact Through Optimized Logistics","year":2025,"lang":"en","type":"article","venue":"GCB Bioenergy","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Biochar; Climate change mitigation; Greenhouse gas; Climate change; Maximization; Global warming","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0004824494,0.0005841494,0.0002620319,0.0003914107,0.0005729388,0.00142966,0.0007465691,0.0003951399,0.002937889],"category_scores_gemma":[0.0006082919,0.0001941343,0.0003371496,0.0007000357,0.0003943,0.0009874391,0.0007296883,0.000392374,0.0004289017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002853803,"about_ca_system_score_gemma":0.003541899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0407548,"about_ca_topic_score_gemma":0.06168333,"domain_scores_codex":[0.9997476,0.00005714508,0.000007196403,0.00004268115,0.00004824744,0.00009718314],"domain_scores_gemma":[0.9997724,0.00005521882,0.00004093989,0.00003480878,0.00006690334,0.00002977784],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000117858,0.00008808661,0.003124935,0.00007279316,0.00002232897,0.00007369921,0.00002270501,0.9556527,0.01471481,0.006085154,0.0006850823,0.01933991],"study_design_scores_gemma":[0.0000278723,0.0002554268,0.002777095,0.0000215588,0.00006345101,0.00004959595,0.0002514183,0.9536961,0.02679742,0.007322258,0.008707887,0.0000298179],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6974272,0.0007101067,0.2513707,0.0008850354,0.00007522324,0.0001977666,0.0006102727,0.0006826643,0.04804095],"genre_scores_gemma":[0.9812393,0.0001904503,0.01443375,0.00003273763,0.000003807526,0.00002525034,0.0001069849,0.00002583997,0.003941724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0407548,"threshold_uncertainty_score":0.08103514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902597655242897,"score_gpt":0.2910102428171081,"score_spread":0.2719842662646791,"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."}}