{"id":"W2039732036","doi":"10.1007/s00267-008-9218-z","title":"Assessing the Effectiveness of a Constructed Arctic Stream Using Multiple Biological Attributes","year":2008,"lang":"en","type":"article","venue":"Environmental Management","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; Parks Canada; Trent University; Ministry of Natural Resources and Forestry","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"STREAMS; Riparian zone; Stream restoration; Environmental science; Large woody debris; Habitat; Ecology; Ecosystem; Natural (archaeology); Hydrology (agriculture); Coarse woody debris; Stream bed; River ecosystem; Geography; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002923772,0.0001301421,0.0001555744,0.00001912972,0.0004830786,0.000007151908,0.0001890258,0.00004587109,0.0005267862],"category_scores_gemma":[0.00001898646,0.00008960191,0.00006511434,0.00009423833,0.001316997,0.0001244796,0.0007056792,0.00008303601,0.00009321975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002048572,"about_ca_system_score_gemma":0.000001222524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007103066,"about_ca_topic_score_gemma":0.000004081954,"domain_scores_codex":[0.9989787,0.000238817,0.000141645,0.0002568559,0.0001749434,0.0002090624],"domain_scores_gemma":[0.9994485,0.0002735775,0.00008017082,0.000166719,0.000001051537,0.00003003228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002717874,0.0001645389,0.9919707,0.0000130169,0.00007463701,0.0000305306,0.00005972415,0.000433868,0.006722147,0.00001973284,0.00003497819,0.0004490178],"study_design_scores_gemma":[0.0004502145,0.00006059906,0.9959825,0.0000134407,0.00003939424,0.00001929699,0.0009427919,0.0001801149,0.001974498,0.0000864408,0.000141885,0.0001088081],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980853,0.00004744417,0.000285048,0.00002584352,0.00006897333,0.0003602419,0.00001194301,0.00001585294,0.001099344],"genre_scores_gemma":[0.9985396,0.00008608014,0.00126506,0.00004898748,0.000006706327,0.000009942125,0.00001101881,0.000003787751,0.00002882864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004747648,"threshold_uncertainty_score":0.576794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0349578276250876,"score_gpt":0.2302091722765532,"score_spread":0.1952513446514656,"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."}}