{"id":"W4220838995","doi":"10.5194/egusphere-egu22-6465","title":"Restored fen vegetation following in situ well pad disturbances","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Northern Alberta Institute of Technology; Université Laval; Center for Northern Studies","funders":"","keywords":"Peat; Revegetation; Oil sands; Environmental science; Vegetation (pathology); Hydrology (agriculture); Environmental engineering; Asphalt; Geology; Land reclamation; Ecology; Geotechnical engineering; Geography; Biology","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":[0.0002892452,0.000300311,0.0003232152,0.0004748541,0.0007721364,0.0006640343,0.0005152957,0.0003071873,0.0009298836],"category_scores_gemma":[0.0004625659,0.0001141062,0.0002428155,0.0003886857,0.000632274,0.0002019047,0.0003751427,0.0004184876,0.0001712612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002668243,"about_ca_system_score_gemma":0.001620871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1303709,"about_ca_topic_score_gemma":0.4236937,"domain_scores_codex":[0.9997434,0.00001843973,0.000007332558,0.00005270166,0.00009032142,0.000087687],"domain_scores_gemma":[0.999625,0.00003318005,0.00008957109,0.00002044097,0.000105908,0.0001258527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005993089,0.002444021,0.4694306,0.000578632,0.0002145602,0.004542887,0.008090949,0.004579915,0.4194573,0.0005439484,0.001127134,0.082997],"study_design_scores_gemma":[0.00001208708,0.001263034,0.9813132,0.00002011987,0.000029307,0.0002398065,0.002872796,0.0006931812,0.0108707,0.00005675473,0.002612592,0.00001643838],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985057,0.00008414653,0.0001940389,0.000007054707,0.000006422225,0.00004899604,0.0001485512,0.00001184081,0.0009933567],"genre_scores_gemma":[0.9971237,0.00008126791,0.0007228403,0.00002482527,0.000002623275,0.0000356952,0.000312551,0.000006115553,0.001690385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1303709,"threshold_uncertainty_score":0.2592241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01179179803954743,"score_gpt":0.2447509692228044,"score_spread":0.232959171183257,"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."}}