{"id":"W3083938359","doi":"10.1016/j.tree.2020.07.014","title":"Converting Ecological Currencies: Energy, Material, and Information Flows","year":2020,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Global Energy and Sustainability Research","field":"Energy","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Ecology; Energy (signal processing); Geography; Environmental science; Environmental resource management; Biology; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004964684,0.0004088224,0.0013418,0.0006511586,0.0001618435,0.0000562447,0.0003173502,0.001034106,0.0007554798],"category_scores_gemma":[0.0005633511,0.000360583,0.0002040152,0.0008953648,0.0002199135,0.0005388255,0.0003714092,0.0005404892,0.0000918506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00132387,"about_ca_system_score_gemma":0.0003424051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007322045,"about_ca_topic_score_gemma":0.002988296,"domain_scores_codex":[0.9968601,0.0008069177,0.0009980794,0.0004718478,0.0001925621,0.0006705248],"domain_scores_gemma":[0.9989778,0.0002346331,0.0002829859,0.0002617024,0.00009348149,0.0001493653],"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":[0.00002902955,0.00006259129,0.0001576746,0.001291818,0.00004546635,0.00001947595,0.00005602734,0.0001425787,1.215404e-7,0.05341954,0.0002617591,0.9445139],"study_design_scores_gemma":[0.0002994119,0.0001923869,0.001308833,0.0002251643,0.00009502099,0.00004714708,0.00008091547,0.001948265,2.411103e-7,0.002239536,0.9932506,0.0003124651],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001785967,0.9846154,0.00003589272,0.0003096581,0.001193201,0.0003207135,0.0000883986,0.0002399865,0.01141081],"genre_scores_gemma":[0.01968739,0.9785147,0.00006501945,0.00007405785,0.0001677398,0.0003211027,0.0009358227,0.00002145307,0.0002126934],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9929888,"threshold_uncertainty_score":0.9998846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02709651482542471,"score_gpt":0.3144995319030053,"score_spread":0.2874030170775806,"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."}}