{"id":"W4396870633","doi":"10.59490/coastlab.2024.743","title":"Seasonal Variation Of Wave Attenuation Capacity Of Canadian Saltmarsh Vegetation","year":2024,"lang":"en","type":"article","venue":"Proceedings of the ... International Conference on the Application of Physical Modelling in Coastal and Port Engineering and Science.","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; École de Technologie Supérieure; Institut National de la Recherche Scientifique","funders":"","keywords":"Salt marsh; Attenuation; Vegetation (pathology); Environmental science; Variation (astronomy); Seasonality; Atmospheric sciences; Physical geography; Geology; Climatology; Hydrology (agriculture); Remote sensing; Geography; Oceanography; Ecology; Physics; Biology; Geotechnical engineering; Optics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002052095,0.0002544762,0.0001986651,0.0008179827,0.001073394,0.0006849435,0.0005310825,0.0002045079,0.002015735],"category_scores_gemma":[0.0008558085,0.0001204411,0.0002346295,0.001237843,0.0004620324,0.000268874,0.0003504489,0.000359715,0.0003188891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008565474,"about_ca_system_score_gemma":0.005246643,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9732767,"about_ca_topic_score_gemma":0.991172,"domain_scores_codex":[0.9997687,0.000009275168,0.000005656424,0.00005290351,0.00009912553,0.00006440504],"domain_scores_gemma":[0.9987724,0.0000510048,0.0000734479,0.00003594308,0.0009427277,0.0001243873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004558662,0.00004882586,0.9255692,0.0001092963,0.000140742,0.0002399054,0.003567822,0.001300059,0.02173911,0.0004395564,0.006073962,0.04031566],"study_design_scores_gemma":[0.000002237539,0.000008816817,0.9966427,0.000008487642,0.00001387252,0.00002180007,0.0007703315,0.0005572847,0.000309655,0.00001452428,0.001638594,0.00001169324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926434,0.0003172135,0.0002718607,0.0001208323,0.0000126141,0.00001019165,0.00207557,0.00002853993,0.004519734],"genre_scores_gemma":[0.9971794,0.0001177542,0.0002075454,0.00003357979,0.000002196791,0.000005145019,0.0009794171,0.000009148305,0.001465986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02672327,"threshold_uncertainty_score":0.06214714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02074641209237388,"score_gpt":0.2085381286356777,"score_spread":0.1877917165433039,"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."}}