{"id":"W2287619839","doi":"10.1016/j.jenvman.2016.02.023","title":"Vegetation community composition in wetlands created following oil sand mining in Alberta, Canada","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Hydrocarbon exploration and reservoir analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor; Alberta Biodiversity Monitoring Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta; Syncrude","keywords":"Wetland; Vegetation (pathology); Environmental science; Composition (language); Oil spill; Geography; Environmental protection; Hydrology (agriculture); Ecology; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002121221,0.0001701447,0.0002416359,0.001661677,0.002317354,0.0009907584,0.0007127802,0.0003340849,0.001179186],"category_scores_gemma":[0.000563512,0.0001998878,0.0002247575,0.002104942,0.0007899489,0.0002453676,0.0006832116,0.0002508517,0.0001573434],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01276647,"about_ca_system_score_gemma":0.01001897,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9863778,"about_ca_topic_score_gemma":0.9973284,"domain_scores_codex":[0.9997329,0.00002012276,0.00001010306,0.00003877459,0.00008244795,0.0001156101],"domain_scores_gemma":[0.9994318,0.00003906968,0.00006930959,0.00001082543,0.0002760253,0.0001728545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003661814,0.0000997179,0.9706809,0.00005993162,0.00006084894,0.0005223664,0.005232816,0.0004869758,0.003823686,0.0002050006,0.0008782002,0.01758338],"study_design_scores_gemma":[0.000002554925,0.00001135131,0.9950488,0.00001107404,0.000007445562,0.00004100491,0.004062767,0.0002658146,0.0001056647,0.0000142886,0.000423776,0.000005269623],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989103,0.000091873,0.00003843301,0.00002889787,0.000002299572,0.000008130345,0.0003197302,0.000002616559,0.0005977224],"genre_scores_gemma":[0.9978707,0.0001314115,0.0001651782,0.00002095843,0.000001586052,0.000006026745,0.0003668096,0.000002213207,0.001435176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01362216,"threshold_uncertainty_score":0.09262764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005200884321128504,"score_gpt":0.1809017792588272,"score_spread":0.1757008949376987,"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."}}