{"id":"W1967133845","doi":"10.5558/tfc86043-1","title":"Assessing forest biomass for bioenergy: Operational challenges and cost considerations","year":2010,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"FPInnovations","keywords":"Environmental science; Biomass (ecology); Bioenergy; Black spruce; Agroforestry; Logging; Taiga; Forestry; Slash (logging); Sustainable forest management; Forest management; Biofuel; Agronomy; Geography; Engineering; Waste management","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.002324006,0.0006414213,0.0004797826,0.001117107,0.0005654896,0.002525241,0.001155278,0.000626871,0.002116413],"category_scores_gemma":[0.004107323,0.0003260912,0.0004887534,0.001725733,0.0005878553,0.002370907,0.0007677188,0.0004097992,0.0002675728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003773584,"about_ca_system_score_gemma":0.002908084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09607753,"about_ca_topic_score_gemma":0.2515846,"domain_scores_codex":[0.9991371,0.0002035056,0.0000460395,0.00007125014,0.0004389981,0.000103008],"domain_scores_gemma":[0.997978,0.001082993,0.0001892212,0.0001279941,0.0005264306,0.00009525532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003680187,0.000170191,0.1679452,0.0008700994,0.0002222589,0.0009880376,0.0009142269,0.4767004,0.01676871,0.014608,0.003059209,0.3173857],"study_design_scores_gemma":[0.00004785638,0.0006529356,0.2775853,0.0006498451,0.0002040489,0.001119781,0.01018741,0.6343691,0.01241884,0.03136163,0.03119282,0.0002103411],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8959227,0.002950536,0.05719769,0.00308294,0.00003805198,0.0003807563,0.002346331,0.0001627901,0.03791833],"genre_scores_gemma":[0.9719362,0.0009908392,0.02461402,0.00006022468,0.00001018483,0.00005696969,0.0005406366,0.00003550076,0.001755459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09607753,"threshold_uncertainty_score":0.1910366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03706175009334738,"score_gpt":0.2734815350379547,"score_spread":0.2364197849446073,"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."}}