{"id":"W4235644849","doi":"10.5194/bg-2019-296","title":"Spatial variations of CO <sub>2</sub> fluxes in the Saguenay Fjord (Québec, Canada) and results of a water mixing model","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; McGill University","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Université du Québec à Montréal; Natural Sciences and Engineering Research Council of Canada; Marine Environmental Observation Prediction and Response Network; McGill University","keywords":"Fjord; Brackish water; Oceanography; Estuary; Seawater; Tributary; Surface water; Geology; Dissolved organic carbon; Water column; Bay; Hydrology (agriculture); Environmental science; Salinity; Geography","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":[0.0002499767,0.0006668094,0.0002980394,0.0004361932,0.001039121,0.0009829688,0.001163293,0.0007549598,0.001618069],"category_scores_gemma":[0.0004514238,0.0002763865,0.0005742892,0.0008189486,0.00042729,0.0002655099,0.0002743466,0.0004685051,0.0001861737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01296459,"about_ca_system_score_gemma":0.005392948,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9877083,"about_ca_topic_score_gemma":0.9785293,"domain_scores_codex":[0.9999131,0.00001058483,0.000004136558,0.00002811436,0.00001270008,0.00003128768],"domain_scores_gemma":[0.9997588,0.00004831189,0.00001948172,0.00001350875,0.0001140226,0.0000458952],"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":[0.0006791215,0.0002422423,0.2362776,0.000089508,0.0002540055,0.000556147,0.00027926,0.7296554,0.01335126,0.001071794,0.004113231,0.01343049],"study_design_scores_gemma":[0.00009737012,0.00002783126,0.130719,0.00001579719,0.00005419432,0.00002223901,0.000194584,0.8664212,0.001247613,0.00007758923,0.001084518,0.0000381651],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950914,0.00009818571,0.0006258655,0.00009642667,0.000009803951,0.00001712137,0.002137596,0.0001283307,0.001795132],"genre_scores_gemma":[0.9963638,0.00004976763,0.0007818296,0.00002512877,0.000001763983,0.00001121218,0.001851634,0.00001896982,0.0008957541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01296459,"threshold_uncertainty_score":0.09406513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01128413431363947,"score_gpt":0.183599946865472,"score_spread":0.1723158125518325,"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."}}