{"id":"W3036594918","doi":"10.1016/j.envsci.2022.07.020","title":"Evaluating the development and use of a rapid wetland assessment tool (ABWRET-A) in policy implementation in Alberta, Canada","year":2022,"lang":"en","type":"article","venue":"Environmental Science & Policy","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Environment and Protected Areas; University of Waterloo","funders":"Global Water Futures; Alberta Innovates","keywords":"Wetland; Environmental resource management; Environmental planning; Policy development; Environmental policy; Geography; Environmental protection; Environmental science; Political science; Ecology; Public administration","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001330378,0.0001862737,0.0001578308,0.000216336,0.0005265111,0.00004506124,0.0004293238,0.00001678071,0.001424652],"category_scores_gemma":[0.00004759183,0.0001683292,0.00002290986,0.0009112586,0.0005108499,0.0004616875,0.00148358,0.0001832462,0.000006619787],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005255147,"about_ca_system_score_gemma":0.0005036124,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7376393,"about_ca_topic_score_gemma":0.6290986,"domain_scores_codex":[0.9969816,0.0001961578,0.0005379838,0.0004942099,0.001278,0.0005120613],"domain_scores_gemma":[0.9992943,0.0001106396,0.0001986845,0.0002970022,0.000001021043,0.00009837985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002681086,0.0002078156,0.8579838,0.000006426124,0.000007054761,0.000005410467,0.004229936,0.01514996,0.03216346,0.001003294,0.0002322209,0.08898385],"study_design_scores_gemma":[0.0006344343,0.0001190627,0.974802,0.000004259462,0.000003668062,0.000004880828,0.002655986,0.002336303,0.00155214,0.00007702834,0.01761266,0.0001975858],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944972,0.000009787948,0.00001015859,0.00373312,0.00003953742,0.0007030144,0.00001628012,0.000003945565,0.0009869934],"genre_scores_gemma":[0.9956264,0.0000214374,0.001140453,0.002550973,0.0000111272,0.0002142583,0.00001935634,0.00001169401,0.0004042277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1168182,"threshold_uncertainty_score":0.9994882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0261387792948707,"score_gpt":0.3211145610180967,"score_spread":0.294975781723226,"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."}}