{"id":"W4411632577","doi":"10.20944/preprints202506.2079.v1","title":"Biochar Affects Greenhouse Gas Emissions from Urban Forestry Waste","year":2025,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biochar; Greenhouse gas; Environmental science; Forestry; Waste management; Agroforestry; Geography; Engineering; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001825427,0.0003925594,0.0002674701,0.0002328144,0.0002312408,0.0004938706,0.0001868531,0.0003889376,0.000585512],"category_scores_gemma":[0.0001796785,0.0001752945,0.0005603739,0.0002500461,0.0002361833,0.0002315005,0.0002127569,0.0003374921,0.0001536154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003807319,"about_ca_system_score_gemma":0.0002258119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004781735,"about_ca_topic_score_gemma":0.007694715,"domain_scores_codex":[0.9997754,0.00002633277,0.00002008261,0.00006906627,0.00005949963,0.00004965623],"domain_scores_gemma":[0.9998842,0.00002486706,0.00003237233,0.000008238634,0.0000369187,0.00001326646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000359998,0.00008290121,0.007782258,0.000106978,0.00003096849,0.00009493672,0.00003542787,0.001360833,0.9866439,0.00005223754,0.00005783834,0.003391816],"study_design_scores_gemma":[0.00001291132,0.0007678283,0.05925774,0.00002009888,0.00007630651,0.00008034349,0.0001914265,0.002843293,0.9352491,0.00008146875,0.001395861,0.00002367755],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987665,0.0003143572,0.0002437209,0.0000142927,0.000009341182,0.000007670419,0.0002120778,0.00001006989,0.0004221291],"genre_scores_gemma":[0.9983694,0.0003616988,0.000419675,0.00002901469,0.000003058566,0.0000115312,0.0002150157,0.000006993293,0.0005834735],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004781735,"threshold_uncertainty_score":0.009507775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06187331243594889,"score_gpt":0.3070477036231506,"score_spread":0.2451743911872017,"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."}}