{"id":"W1970972990","doi":"10.3390/w6020196","title":"Temporal Variability of Monthly Daily Extreme Water Levels in the St. Lawrence River at the Sorel Station from 1912 to 2010","year":2014,"lang":"en","type":"article","venue":"Water","topic":"Climate variability and models","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Digging; Environmental science; Snow; Climate change; Atlantic multidecadal oscillation; Spring (device); Pacific decadal oscillation; Climatology; Water level; Hydrology (agriculture); North Atlantic oscillation; Watershed; Period (music); Physical geography; Geography; Oceanography; El Niño Southern Oscillation; Geology; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002671912,0.0001224688,0.0001559996,0.0007604887,0.0002744175,0.0005622478,0.0002513871,0.0001650814,0.0007114171],"category_scores_gemma":[0.000626133,0.0000939434,0.0001462668,0.00116421,0.0001975737,0.000214227,0.000435119,0.0002373502,0.0002343654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001056254,"about_ca_system_score_gemma":0.000591372,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1529216,"about_ca_topic_score_gemma":0.3653739,"domain_scores_codex":[0.9998054,0.00002027832,0.00001487623,0.00005584616,0.00005510565,0.00004854304],"domain_scores_gemma":[0.9994191,0.00004493886,0.0001929586,0.00002579869,0.0002558593,0.00006121281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006280722,0.00001875346,0.9909796,0.00002007005,0.00005274397,0.00007942099,0.0005622553,0.000370031,0.0008143143,0.00005922698,0.001322164,0.005658803],"study_design_scores_gemma":[0.000001062258,0.000007566325,0.9983442,0.000003523318,0.000004710609,0.00001524976,0.0001854813,0.0001895704,0.00006808842,0.000005455289,0.001171892,0.000003112578],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957258,0.00008106764,0.00009037076,0.00006045437,0.00000670471,0.000003365086,0.002572903,0.00001574339,0.001443737],"genre_scores_gemma":[0.9955133,0.00007511589,0.0001157392,0.00001874698,0.000010796,0.000009510977,0.003384496,0.000004635492,0.0008677494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8470784,"threshold_uncertainty_score":0.3040629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03591237226210792,"score_gpt":0.2290896568524343,"score_spread":0.1931772845903263,"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."}}