{"id":"W1879031513","doi":"10.1139/er-2014-0082","title":"Comparative study of cold-climate constructed wetland technology in Canada and northern China for water resource protection","year":2015,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Constructed Wetlands for Wastewater Treatment","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fleming College; Queen's University","funders":"Program for New Century Excellent Talents in University","keywords":"Wetland; Environmental science; China; Resource (disambiguation); Sewage treatment; Population; Constructed wetland; Effluent; Water resources; Environmental engineering; Water resource management; Environmental resource management; Environmental protection; Ecology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005251449,0.0003967597,0.0002803267,0.0012487,0.001739165,0.0009173764,0.0005611484,0.000216322,0.0009147157],"category_scores_gemma":[0.0005476534,0.0001040645,0.0003751329,0.002852507,0.0006583824,0.0003283569,0.0004615924,0.0002702603,0.00008402151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02210987,"about_ca_system_score_gemma":0.03254526,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.904286,"about_ca_topic_score_gemma":0.9668276,"domain_scores_codex":[0.9991791,0.00005412295,0.00002459635,0.00008255187,0.0004276742,0.0002319848],"domain_scores_gemma":[0.9995056,0.00003545175,0.00005413289,0.00002016727,0.0002935086,0.0000912021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001102384,0.0006197952,0.1603693,0.005703103,0.0003295201,0.005119865,0.009151228,0.008892432,0.1018443,0.013824,0.008448277,0.6845958],"study_design_scores_gemma":[0.00005311939,0.001059146,0.8043349,0.0003550049,0.000302235,0.001176804,0.01145334,0.003256604,0.04080365,0.0004709092,0.1366039,0.0001302876],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9570554,0.01306525,0.002200982,0.0004292551,0.00004801686,0.0002353508,0.0004643703,0.00005306199,0.02644821],"genre_scores_gemma":[0.9742497,0.01227024,0.002892091,0.00007496848,0.000008468993,0.00005070329,0.0005460843,0.0000122301,0.00989552],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.09571403,"threshold_uncertainty_score":0.1925554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01601086136732311,"score_gpt":0.217033141998506,"score_spread":0.2010222806311829,"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."}}