{"id":"W2991516990","doi":"","title":"Adapting regional watershed management to climate change in Bavaria and Québec","year":2013,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Climate change; Watershed; Geography; Environmental science; Physical geography; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000224443,0.0001737888,0.0001792252,0.00006367014,0.0000886753,0.00008278017,0.0001922203,0.00007347517,0.001066941],"category_scores_gemma":[0.000007362866,0.0001470475,0.00002287679,0.00009866036,0.0000414104,0.0003183221,0.0002859115,0.0001063745,0.0008320282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009708144,"about_ca_system_score_gemma":0.0000098156,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0378002,"about_ca_topic_score_gemma":0.04276047,"domain_scores_codex":[0.9985884,0.00003677767,0.0002639095,0.0004123689,0.0001704703,0.0005280853],"domain_scores_gemma":[0.9995359,0.00002349201,0.00006631389,0.0001661913,0.000009717131,0.0001984522],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006582181,0.000211035,0.8320757,0.00003651493,0.00002810563,0.0001576906,0.002876529,0.001237255,0.04016745,0.002278222,0.007088515,0.1137772],"study_design_scores_gemma":[0.0003430659,0.00007246033,0.99348,0.00002073,0.000004841869,0.000009357472,0.00007449102,0.001518751,0.000199753,0.00023959,0.003825371,0.0002115566],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978852,0.00001097494,0.00001694844,0.005531852,0.00006260072,0.0003883273,0.000001787604,0.00002640061,0.01510912],"genre_scores_gemma":[0.9957997,0.00006914699,0.00177695,0.0015535,0.00007407147,0.000168436,0.00001435827,0.00001075833,0.0005331466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1614043,"threshold_uncertainty_score":0.9999459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02767382644484086,"score_gpt":0.242109780813527,"score_spread":0.2144359543686861,"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."}}