{"id":"W3191570047","doi":"10.1080/21664250.2021.1894815","title":"Quantifying blue carbon for the largest salt marsh in southern British Columbia: implications for regional coastal management","year":2021,"lang":"en","type":"article","venue":"Coastal Engineering Journal","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Mitacs","keywords":"Salt marsh; Blue carbon; Environmental science; Marsh; Carbon fibers; Oceanography; Hydrology (agriculture); Geography; Carbon sequestration; Ecology; Geology; Wetland; Carbon dioxide; Mathematics; Biology; Geotechnical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004344143,0.0001288903,0.0001834662,0.00002997913,0.0002891848,0.0003730881,0.0002603033,0.0000615399,0.00006380855],"category_scores_gemma":[0.00006584982,0.0001611711,0.0001367941,0.0002234719,0.00003260641,0.00009919702,0.0002541135,0.0002248418,0.000004453392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001482439,"about_ca_system_score_gemma":0.00002839711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001839543,"about_ca_topic_score_gemma":0.2916969,"domain_scores_codex":[0.9987082,0.00001808488,0.0003554079,0.0002707501,0.0001916783,0.0004558333],"domain_scores_gemma":[0.9993721,0.0001809519,0.00009444586,0.0002046404,0.00003480466,0.0001131],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000114052,0.0004712435,0.3546762,0.0005952615,0.0003470099,0.0002685749,0.0008868353,0.5749858,0.007253481,0.0006270187,0.008424015,0.05135049],"study_design_scores_gemma":[0.003898137,0.0001615259,0.4737688,0.000576497,0.0001545285,0.00324745,0.002657651,0.4766194,0.00003221064,0.0007359574,0.03720837,0.0009394698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8433625,0.0002579998,0.1529423,0.001010835,0.000695191,0.0008815907,0.0005413745,0.00006228625,0.0002459242],"genre_scores_gemma":[0.9919637,0.000117021,0.005593035,0.00005726718,0.0001800642,0.0001781148,0.00006443921,0.00005872775,0.00178756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2898574,"threshold_uncertainty_score":0.7212278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01492575102159994,"score_gpt":0.2167426519182458,"score_spread":0.2018169008966459,"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."}}