{"id":"W2998126453","doi":"","title":"Detection and Attribution of Variability and Trends in Canadian Prairie Provinces' Streamflow","year":2011,"lang":"en","type":"article","venue":"AGUFM","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Streamflow; Geography; Environmental science; Attribution; Climatology; Physical geography; Geology; Cartography; Drainage basin; Psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001327687,0.000169177,0.000143857,0.001383009,0.001330485,0.001179705,0.0006791779,0.0003346064,0.0004285731],"category_scores_gemma":[0.005297702,0.0001963606,0.0001996454,0.001686847,0.0004942418,0.0004431234,0.0005182844,0.0004733735,0.00008427428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006612367,"about_ca_system_score_gemma":0.00914408,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.968801,"about_ca_topic_score_gemma":0.9768203,"domain_scores_codex":[0.9995151,0.0000638308,0.00002866327,0.0001308845,0.0001386907,0.0001228414],"domain_scores_gemma":[0.9973053,0.0006536599,0.0003537494,0.0001783693,0.001309096,0.0001998837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005640998,0.00002482516,0.9803815,0.000009154448,0.00003953558,0.00001908983,0.0004817077,0.00114613,0.001484097,0.000195373,0.0005324589,0.01562959],"study_design_scores_gemma":[0.000002179376,0.000004009908,0.9962764,0.000002736964,0.000007582505,0.000007930513,0.0002552301,0.002756771,0.0002027896,0.0000268226,0.0004530178,0.000004458103],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972984,0.00008651458,0.0004376851,0.0000907969,0.000004762202,0.0000122666,0.000790693,0.00002191563,0.00125696],"genre_scores_gemma":[0.998194,0.00004918826,0.0007002428,0.0000126208,0.000002524805,0.000005223577,0.0006377562,0.000004497339,0.0003939922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03119904,"threshold_uncertainty_score":0.06276548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136213823248093,"score_gpt":0.2014657075102128,"score_spread":0.1901035692777319,"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."}}