{"id":"W4378229365","doi":"10.3390/f14061090","title":"Can Wood Pellets from Canada’s Boreal Forest Reduce Net Greenhouse Gas Emissions from Energy Generation in the UK?","year":2023,"lang":"en","type":"article","venue":"Forests","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Forest Research Institute; Ministry of Natural Resources and Forestry","funders":"Ontario Ministry of Natural Resources and Forestry; Ministry of Natural Resources","keywords":"Environmental science; Greenhouse gas; Slash (logging); Life-cycle assessment; Climate change; Global warming; Biomass (ecology); Pellets; Forestry; Production (economics); Agronomy; Ecology","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":[0.0003973623,0.0004168371,0.0002245846,0.0003015064,0.001107966,0.001302602,0.0006341602,0.0003826024,0.00197443],"category_scores_gemma":[0.0009375067,0.0001494802,0.000347429,0.0005645934,0.0005559691,0.0004144878,0.0004125304,0.0003004742,0.0002099079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01099653,"about_ca_system_score_gemma":0.01179802,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9590315,"about_ca_topic_score_gemma":0.9904408,"domain_scores_codex":[0.9995493,0.00005215061,0.00001251693,0.0000547265,0.0001393319,0.0001919682],"domain_scores_gemma":[0.9995389,0.00005661009,0.00007146556,0.00001932096,0.0002124704,0.0001012827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.005049513,0.0008455066,0.588995,0.00206947,0.0007615007,0.004196694,0.00300886,0.02844746,0.0549973,0.003398775,0.01329259,0.2949373],"study_design_scores_gemma":[0.000134078,0.001015367,0.9423561,0.0001915995,0.0003156974,0.0002451854,0.006833015,0.004617333,0.01170543,0.0004552709,0.03206268,0.00006822879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882266,0.002481327,0.0003924896,0.001023329,0.0000300754,0.00003909139,0.0008233764,0.00001708179,0.006966632],"genre_scores_gemma":[0.9937947,0.001898075,0.0006980288,0.0003424041,0.000006592663,0.00001355644,0.0004607377,0.0000087865,0.002777217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04096854,"threshold_uncertainty_score":0.08241957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01575113048171876,"score_gpt":0.2112027668922155,"score_spread":0.1954516364104968,"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."}}