{"id":"W4322581825","doi":"10.1525/elementa.2022.00076","title":"Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment","year":2023,"lang":"en","type":"article","venue":"Elementa Science of the Anthropocene","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski; Manitoba Hydro; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Hydro","keywords":"Colored dissolved organic matter; Bay; River mouth; Plume; Discharge; Hydrology (agriculture); Environmental science; Moderate-resolution imaging spectroradiometer; Oceanography; River delta; Tributary; Geology; Sediment; Drainage basin; Satellite; Delta; Geomorphology; Phytoplankton; Geography; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000211766,0.0002525749,0.000183562,0.0005552081,0.0002927113,0.0005351158,0.0002248578,0.0001177199,0.0004126644],"category_scores_gemma":[0.0004275167,0.0002003828,0.00023012,0.0005782229,0.0001596372,0.0002478245,0.0004144429,0.0002503237,0.00005067157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001229992,"about_ca_system_score_gemma":0.001043051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.321054,"about_ca_topic_score_gemma":0.4424742,"domain_scores_codex":[0.9999226,0.000006258294,0.000006181232,0.00003171593,0.00002061844,0.00001255746],"domain_scores_gemma":[0.9998314,0.00002770583,0.00003458219,0.000008787022,0.00006124016,0.00003623318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002306381,0.00005001731,0.9483894,0.00003561958,0.00006904596,0.0003001746,0.001053489,0.002002347,0.02414846,0.00008787048,0.0003499693,0.02328291],"study_design_scores_gemma":[0.00001050655,0.00005715202,0.9923019,0.000008411574,0.00001867491,0.00003926249,0.0005947577,0.005094908,0.001407268,0.00002382165,0.0004345447,0.000008720408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992223,0.00004052007,0.000217993,0.00001429544,0.000003084641,0.000007235055,0.0002310036,0.00001433463,0.000249342],"genre_scores_gemma":[0.9973852,0.00006794294,0.001319783,0.00001877337,0.000002987295,0.00001062551,0.0006198379,0.000004436931,0.0005704915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.321054,"threshold_uncertainty_score":0.6383706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01590441133086274,"score_gpt":0.2511045371787272,"score_spread":0.2352001258478644,"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."}}