{"id":"W3023866727","doi":"10.1007/s00027-020-00721-3","title":"Emission of greenhouse gases from French temperate hydropower reservoirs","year":2020,"lang":"en","type":"article","venue":"Aquatic Sciences","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"EnGlobe (Canada); Espace pour la vie","funders":"Électricité de France","keywords":"Environmental science; Hydrology (agriculture); Greenhouse gas; Hydropower; Discharge; Particulates; Organic matter; Geology; Ecology; Drainage basin; Oceanography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003138595,0.0001098864,0.0002001318,0.00004831612,0.0001581425,0.00006839509,0.000470309,0.00003497169,0.004140091],"category_scores_gemma":[0.0002360997,0.00007519221,0.00004820798,0.0005546127,0.0002036977,0.0002716361,0.00003635849,0.0000672037,0.0002819576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001205988,"about_ca_system_score_gemma":0.0001006703,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04838284,"about_ca_topic_score_gemma":0.007058214,"domain_scores_codex":[0.9985686,0.00008651838,0.0002997721,0.0003191274,0.0005071335,0.0002188246],"domain_scores_gemma":[0.99929,0.0002320775,0.0001235487,0.0001505781,0.00002181737,0.0001819035],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001485845,0.00001464103,0.980113,0.00002264612,0.00001055772,0.000009567832,0.0007801266,0.0009070761,0.0007608928,0.00001249659,0.003234974,0.01411919],"study_design_scores_gemma":[0.0007469014,0.001927788,0.2231102,0.0002146622,0.00004908098,0.000008337556,0.003767713,0.7423965,0.01364897,0.004938263,0.008481474,0.000710102],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9813382,0.0003749827,0.00006797451,0.001112239,0.0001565587,0.00009813846,0.00004234302,0.00003317997,0.01677639],"genre_scores_gemma":[0.9988267,0.00003197862,0.0004666228,0.0003372925,0.00009541493,5.183543e-7,0.00002126097,0.000001915134,0.0002183392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7570028,"threshold_uncertainty_score":0.9967703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03009376122671612,"score_gpt":0.2310382213009246,"score_spread":0.2009444600742085,"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."}}