{"id":"W4413007063","doi":"10.3390/land14081605","title":"Biochar Affects Greenhouse Gas Emissions from Urban Forestry Waste","year":2025,"lang":"en","type":"article","venue":"Land","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biochar; Greenhouse gas; Environmental science; Urban forestry; Environmental protection; Forestry; Carbon sequestration; Charcoal; Waste management; Agroforestry; Environmental engineering; Carbon dioxide; Pyrolysis; Geography; Chemistry; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006624733,0.0001074675,0.0001045043,0.00002574143,0.0001021176,0.00002979209,0.0002779796,0.00004972861,0.001480093],"category_scores_gemma":[0.00001827111,0.00008879114,0.00003790085,0.0001658074,0.00005608406,0.0000573901,0.0004946483,0.00008916754,0.000458676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005805125,"about_ca_system_score_gemma":0.000003879902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003190214,"about_ca_topic_score_gemma":0.001851925,"domain_scores_codex":[0.9992461,0.00003200576,0.00009340895,0.0002496234,0.0001565058,0.0002223776],"domain_scores_gemma":[0.9994255,0.00004253023,0.00003052612,0.0004094708,0.000001107893,0.00009091214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000308053,0.0001302157,0.8591225,0.00002254892,0.0000495235,0.00003879814,0.0003518957,0.00731721,0.002132046,0.0001972404,0.1254179,0.005189229],"study_design_scores_gemma":[0.003866178,0.0002626682,0.3571987,0.000476319,0.0002525917,0.000002611908,0.0006684481,0.0580225,0.01180303,0.008238973,0.5579947,0.001213275],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9642345,0.0001253675,0.0002570105,0.0004183294,0.0001556167,0.0001852201,0.00001267949,0.00004848397,0.03456274],"genre_scores_gemma":[0.9910646,0.00002816968,0.0002121522,0.0003560161,0.00005344972,0.000014024,0.00001321852,0.00001000095,0.00824836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5019239,"threshold_uncertainty_score":0.9994327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007928786378513955,"score_gpt":0.2241361722192915,"score_spread":0.2162073858407775,"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."}}