{"id":"W7097506966","doi":"","title":"Biopower generation from mountain pine infested wood in Canada: An economical opportunity for greenhouse gas mitigation","year":2007,"lang":"en","type":"article","venue":"","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biopower; Greenhouse gas; Institution; Reproduction; Greenhouse; Information Dissemination","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0001186494,0.0001489423,0.0001307164,0.0002793257,0.001323633,0.0006463909,0.0003075026,0.0002027688,0.004326524],"category_scores_gemma":[0.0001286408,0.00007147584,0.0001767976,0.0003216202,0.0002795276,0.0002263763,0.000237536,0.0002222603,0.0002708477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004448181,"about_ca_system_score_gemma":0.003716064,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6610647,"about_ca_topic_score_gemma":0.9002807,"domain_scores_codex":[0.999889,0.000006130291,0.000001264194,0.00001333093,0.00004778761,0.00004236183],"domain_scores_gemma":[0.9999545,0.000006511199,0.000003506799,0.000002341377,0.00001849888,0.0000147208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002538282,0.000606577,0.1260125,0.0004897909,0.00008533691,0.005131671,0.002716115,0.0162673,0.3962804,0.004693846,0.009635208,0.435543],"study_design_scores_gemma":[0.0001452409,0.001434647,0.5974553,0.0001520104,0.0002280006,0.001265186,0.012636,0.04843984,0.2201224,0.002424344,0.1155598,0.0001371549],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885569,0.000476353,0.00156699,0.0001578649,0.00001498885,0.0000339911,0.0002652073,0.00004111696,0.008886606],"genre_scores_gemma":[0.9904671,0.0002654345,0.0008835625,0.00001731179,0.00000213753,0.000005887872,0.0001698658,0.00001271566,0.008175945],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3389353,"threshold_uncertainty_score":0.6818627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01859047224712122,"score_gpt":0.2273891547421751,"score_spread":0.2087986824950539,"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."}}