{"id":"W2382594364","doi":"","title":"Status and Trends of Biomass Energy Based on Bibliometrics","year":2014,"lang":"en","type":"article","venue":"Anhui nongye kexue","topic":"Power Systems and Renewable Energy","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biomass (ecology); Bibliometrics; China; Subject (documents); Index (typography); Web of science; Energy (signal processing); Environmental science; Environmental resource management; Agricultural engineering; Computer science; Geography; Ecology; Political science; Library science; Mathematics; Biology; Statistics; World Wide Web; Engineering; MEDLINE","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["bibliometrics"],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["bibliometrics"],"domain":null,"study_design":"design_other","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002878883,0.0002442709,0.0004034325,0.005860019,0.00007940497,0.00004887824,0.0001894982,0.0001968658,0.0001456132],"category_scores_gemma":[0.00009207639,0.0001985502,0.000105091,0.006996493,0.00008988265,0.00009511915,0.00005524488,0.00006997351,0.000009062009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003245004,"about_ca_system_score_gemma":0.0000355573,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01995158,"about_ca_topic_score_gemma":0.001937603,"domain_scores_codex":[0.9982626,0.0001372538,0.0003811214,0.0003775222,0.0003865866,0.0004548787],"domain_scores_gemma":[0.9986945,0.0002666239,0.0001794851,0.0005342118,0.00008832083,0.0002368778],"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":[0.0002779504,0.0008274476,0.01756326,0.0002777529,0.0002715113,0.00004188568,0.0001767654,0.01756828,0.02618929,0.1971518,0.01659385,0.7230603],"study_design_scores_gemma":[0.002163334,0.0008909769,0.01654375,0.00008728602,0.00003903019,0.000005897286,0.00003601275,0.02341525,0.04864138,0.0006235022,0.9070165,0.0005370891],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3979009,0.001852619,0.01587851,0.0003584194,0.002611753,0.00008080082,0.00007576446,0.0003066011,0.5809346],"genre_scores_gemma":[0.9941358,0.00009496854,0.0002823272,0.0002399463,0.0002056373,0.00001153531,0.00004201084,0.0000447122,0.004943043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8904226,"threshold_uncertainty_score":0.9865746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01290077507938273,"score_gpt":0.2363300080788458,"score_spread":0.2234292329994631,"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."}}