{"id":"W4319082699","doi":"10.21083/surg.v15i1.7167","title":"Predicting The Great Lakes Wetlands' Resilience to Climate Change in Response to Phragmites australis subsp. australis Removal","year":2023,"lang":"en","type":"article","venue":"SURG Journal","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Phragmites; Wetland; Environmental science; Climate change; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001248977,0.0002620271,0.0002309121,0.001511716,0.0001933864,0.0007287269,0.0002464698,0.0002871559,0.00105055],"category_scores_gemma":[0.003623537,0.0001335184,0.0009781641,0.00103059,0.0001667105,0.000688863,0.0003779413,0.0003205069,0.0001136318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005389202,"about_ca_system_score_gemma":0.001231385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02681274,"about_ca_topic_score_gemma":0.07416663,"domain_scores_codex":[0.9997299,0.00008981334,0.00004659353,0.00005104455,0.00005059363,0.00003198713],"domain_scores_gemma":[0.9977246,0.001144945,0.0005826061,0.00004264527,0.0003869616,0.0001183761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004056017,0.0001358888,0.8530686,0.007990207,0.001715078,0.001046559,0.001356387,0.008924649,0.005696272,0.000604889,0.004178147,0.1148775],"study_design_scores_gemma":[0.00001873343,0.0003135873,0.9820104,0.0008068954,0.001084674,0.0001961244,0.001846969,0.006253844,0.0009733443,0.0004571319,0.006007029,0.00003126075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762734,0.01425061,0.001240668,0.00134694,0.0000598875,0.00008340352,0.003933869,0.00003805346,0.002773103],"genre_scores_gemma":[0.9894991,0.006165106,0.001663538,0.0001361949,0.00004606985,0.00008700128,0.001912747,0.000007311288,0.0004828866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9731873,"threshold_uncertainty_score":0.05331331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02842226871202411,"score_gpt":0.2841850100473304,"score_spread":0.2557627413353062,"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."}}