{"id":"W4411641387","doi":"10.1080/07011784.2025.2519131","title":"A climatological approach to predicting water level of Great Slave Lake","year":2025,"lang":"en","type":"article","venue":"Canadian Water Resources Journal / Revue canadienne des ressources hydriques","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Northwest Territories; University of Calgary","funders":"","keywords":"Environmental science; Climatology; Hydrology (agriculture); Meteorology; Physical geography; Geology; Geography; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0001726181,0.0002932562,0.0001317759,0.0005525632,0.0005316318,0.0007586643,0.0005735084,0.0004119786,0.0011346],"category_scores_gemma":[0.0006808602,0.0001901609,0.0002741184,0.0006105796,0.0002069775,0.000288352,0.0003171201,0.0004389828,0.0001513968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001974727,"about_ca_system_score_gemma":0.002642858,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5923247,"about_ca_topic_score_gemma":0.5568679,"domain_scores_codex":[0.9999479,0.000007621023,0.00000318551,0.00001914931,0.00001311805,0.000009031013],"domain_scores_gemma":[0.9999008,0.00002144193,0.00001181398,0.000006212133,0.00004491304,0.00001482128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00003731095,0.00006527736,0.07521074,0.00003667068,0.00004330255,0.0001469539,0.0001168085,0.903725,0.001499865,0.001694386,0.001707995,0.01571563],"study_design_scores_gemma":[0.000008260232,0.00001205337,0.01511526,0.000006346751,0.000006586963,0.000008521912,0.00006320888,0.9834059,0.0001975993,0.0002975581,0.0008712941,0.000007402645],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951461,0.0002579751,0.02521779,0.0009274753,0.00005264959,0.0001436387,0.004993268,0.0005641978,0.01638213],"genre_scores_gemma":[0.9915038,0.00009461174,0.00635591,0.00002916798,0.00001007212,0.00003925152,0.0008631092,0.00001394942,0.001090262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4076753,"threshold_uncertainty_score":0.8201523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03114235979266829,"score_gpt":0.2184530835042496,"score_spread":0.1873107237115813,"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."}}