{"id":"W2127415090","doi":"10.1002/hyp.7020","title":"Ten‐year water table recovery after clearcutting and draining boreal forested wetlands of eastern Canada","year":2008,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts (Québec); Ministère des Ressources naturelles et des Forêts","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Clearcutting; Water table; Environmental science; Abies balsamea; Peat; Boreal; Hydrology (agriculture); Wetland; Drainage; Interception; Balsam; Logging; Water level; Forestry; Geology; Ecology; Groundwater; Geography","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":[0.0001266,0.0001292004,0.0002226755,0.00001881178,0.0001281096,0.00001076669,0.0001245912,0.00009370889,0.0006387746],"category_scores_gemma":[0.00008676738,0.00007902668,0.00001867245,0.0001057055,0.000230995,0.0001300117,0.0001956566,0.0001164123,0.00001284813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003054194,"about_ca_system_score_gemma":0.00004159926,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03644155,"about_ca_topic_score_gemma":0.1132519,"domain_scores_codex":[0.9989016,0.00003018244,0.0002124903,0.0002902592,0.0001813743,0.0003841165],"domain_scores_gemma":[0.9996468,0.00008181652,0.00005579487,0.00009970261,0.00001427429,0.0001015795],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001629767,0.0000299525,0.9982072,0.00002905841,0.000007944641,0.00009099564,0.000159114,0.0002151855,0.0001817295,0.000001299555,0.0004804955,0.0004340454],"study_design_scores_gemma":[0.0007929731,0.0007433186,0.9886959,0.00002248914,0.0000192992,0.0001767196,0.00007751969,0.001487292,0.001555674,0.0006395025,0.005484357,0.0003049262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898804,0.00004794766,0.00003384548,0.000213211,0.0000269513,0.00007590833,0.000008526829,0.00002058389,0.009692605],"genre_scores_gemma":[0.9989161,0.00006376717,0.0001401449,0.0003909341,0.00003609039,0.00001728476,0.00001960712,0.000008603361,0.0004074707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07681039,"threshold_uncertainty_score":0.9699749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01076172234220972,"score_gpt":0.1924022259964485,"score_spread":0.1816405036542388,"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."}}