{"id":"W4317254007","doi":"10.3389/fmars.2022.1055384","title":"Transport inventories and exchanges of organic matter throughout the St. Lawrence Estuary continuum (Canada)","year":2023,"lang":"en","type":"article","venue":"Frontiers in Marine Science","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Ministère des Ressources naturelles et des Forêts; Université Laval; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Environment and Climate Change Canada","keywords":"Estuary; Tributary; Environmental science; Organic matter; Hypoxia (environmental); Eutrophication; Hydrology (agriculture); Context (archaeology); Oceanography; Dissolved organic carbon; Turbidity; Nutrient; Ecology; Geography; Geology; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.0002465418,0.000352652,0.000234606,0.002014074,0.00120647,0.0009375875,0.0006629472,0.000271766,0.001409205],"category_scores_gemma":[0.0005338104,0.0003060338,0.0003408835,0.004512078,0.0002506316,0.0002930215,0.0004260015,0.0003017281,0.0003780098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01895076,"about_ca_system_score_gemma":0.0194892,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9934722,"about_ca_topic_score_gemma":0.9972275,"domain_scores_codex":[0.9997098,0.00001039442,0.00002940809,0.00006551205,0.0001241441,0.00006069515],"domain_scores_gemma":[0.9987232,0.00005543806,0.0001819411,0.00004417957,0.0008659022,0.0001293741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009424585,0.00004925372,0.9736756,0.0001065973,0.0001045919,0.0001372621,0.000903815,0.001979523,0.00271866,0.0003210558,0.003510293,0.01639899],"study_design_scores_gemma":[0.000004572757,0.00001320487,0.9900296,0.00002087706,0.00002113186,0.00003272345,0.0005785379,0.001969927,0.0006108737,0.00002467558,0.006680338,0.00001351174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9407916,0.0003208851,0.0005027875,0.00009123282,0.000006344606,0.00006747466,0.05438988,0.0001072,0.003722469],"genre_scores_gemma":[0.9219702,0.0006907091,0.002999648,0.00009284774,0.000005611859,0.0001124001,0.05976193,0.0000346138,0.01433203],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01895076,"threshold_uncertainty_score":0.137498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008066780898937065,"score_gpt":0.1943371230128489,"score_spread":0.1862703421139118,"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."}}