{"id":"W1586088532","doi":"10.1002/wene.157","title":"Recovery rate of harvest residues for bioenergy in boreal and temperate forests: A review","year":2014,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Energy and Environment","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Temperate climate; Bioenergy; Taiga; Boreal; Temperate rainforest; Environmental science; Temperate forest; Agroforestry; Ecology; Forestry; Geography; Renewable energy; Biology; Ecosystem","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0004521935,0.0002013541,0.0004371487,0.00008618849,0.00004224883,0.00001300535,0.00008703525,0.00005186323,0.00002478461],"category_scores_gemma":[0.00001266936,0.0001659596,0.0000694526,0.00007090991,0.00007963711,0.0001156045,0.0001809377,0.00003627104,0.000002129774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003467028,"about_ca_system_score_gemma":0.000002132266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001241717,"about_ca_topic_score_gemma":0.000491899,"domain_scores_codex":[0.9989432,0.00007299156,0.0005126998,0.0002465523,0.00005097367,0.0001735801],"domain_scores_gemma":[0.9995786,0.00003208981,0.00008283741,0.0002340607,0.000004502266,0.00006794097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002549412,0.0003253108,0.009344245,0.02571238,0.000257681,0.00001018235,0.0004980163,0.009769771,0.001705463,0.03646417,0.1039335,0.8117244],"study_design_scores_gemma":[0.0006838996,0.0004190299,0.01431826,0.006239067,0.00007810456,0.000006703671,0.00003174513,0.007167608,0.0005460759,0.003772334,0.9663276,0.0004095907],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.1098248,0.8042138,0.06343888,0.003461759,0.0007694461,0.002977321,0.0000998106,0.0002056331,0.01500857],"genre_scores_gemma":[0.1693033,0.8283245,0.0008428795,0.0003585498,0.00004468151,0.000391844,0.0001154809,0.00003320698,0.0005855195],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8623941,"threshold_uncertainty_score":0.6767638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01144869064753885,"score_gpt":0.2301444301568925,"score_spread":0.2186957395093536,"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."}}