{"id":"W2062414035","doi":"10.1111/j.1744-7976.2012.01246.x","title":"Bioenergy from Mountain Pine Beetle Timber and Forest Residuals: A Cost Analysis","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; Canadian Forest Service","funders":"Ministry of Forests, Lands and Natural Resource Operations; Government of Canada","keywords":"Forestry; Biomass (ecology); Environmental science; Raw material; Geography; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002038228,0.0002706916,0.000500734,0.0005399577,0.0001107957,0.0001496864,0.0002554076,0.0001188215,0.0004589746],"category_scores_gemma":[0.00002423815,0.0002451957,0.0001820675,0.0002521318,0.00007432436,0.0006015707,0.00002121204,0.0001426001,0.00003089037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176222,"about_ca_system_score_gemma":0.00008795231,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03462588,"about_ca_topic_score_gemma":0.9203881,"domain_scores_codex":[0.998458,0.00002205789,0.0006281297,0.0001906249,0.00001377563,0.0006873585],"domain_scores_gemma":[0.9977722,0.00004703011,0.0002208632,0.0001912028,0.00007427856,0.001694431],"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":[0.00002817511,0.00004001933,0.4024653,0.0001014496,0.005960392,0.00008060499,0.003258274,0.4911176,0.0001406108,0.05180424,0.0404931,0.004510276],"study_design_scores_gemma":[0.0007920112,0.00007868851,0.820462,0.00003967129,0.0006818639,0.0001185656,0.001998602,0.004628115,0.000139434,0.0004399711,0.1698817,0.0007393761],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950578,0.001054323,0.00008430464,0.0006340074,0.0008614342,0.0001438469,0.0002613721,0.00001858075,0.001884351],"genre_scores_gemma":[0.9980216,0.0002371016,0.0003285467,0.000181828,0.000570609,0.000009631425,0.0001965039,0.00002670897,0.0004274762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8857622,"threshold_uncertainty_score":0.9998791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142100529602328,"score_gpt":0.1621675001164074,"score_spread":0.1479574471561746,"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."}}