{"id":"W2981420928","doi":"10.4095/299802","title":"Wetland ecohydrology monitoring at TRCA: insights and lessons learned","year":2017,"lang":"en","type":"report","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ecohydrology; Wetland; Environmental science; Hydrology (agriculture); Water resource management; Ecosystem; Ecology; Geology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001560589,0.0003659507,0.0001957618,0.001167038,0.0008599816,0.001662018,0.0007677148,0.0004819739,0.002044382],"category_scores_gemma":[0.00252981,0.0001612928,0.0001964001,0.001617222,0.001024193,0.00135143,0.0008805002,0.0007760955,0.0003036593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00798778,"about_ca_system_score_gemma":0.0158872,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8260013,"about_ca_topic_score_gemma":0.9482803,"domain_scores_codex":[0.9989738,0.0001796872,0.00002508488,0.0001130417,0.0004985622,0.0002097091],"domain_scores_gemma":[0.9972139,0.0004164646,0.0001863671,0.0001900822,0.001502307,0.0004909838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001097984,0.0001963636,0.5177682,0.0004571438,0.00005226712,0.001460245,0.008497367,0.005349298,0.009259919,0.006229694,0.04831851,0.4023012],"study_design_scores_gemma":[0.00002225758,0.0001986735,0.8020281,0.000368704,0.00005848576,0.0005256576,0.02417017,0.009994091,0.005187282,0.002577387,0.1547842,0.00008491],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8158386,0.008337029,0.01724222,0.05408428,0.0003435108,0.0004590709,0.01119041,0.0006310961,0.0918738],"genre_scores_gemma":[0.9445653,0.006411674,0.03008544,0.001195513,0.0001653459,0.0001075254,0.002900546,0.0001010275,0.01446761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1739987,"threshold_uncertainty_score":0.3500467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06260847542698524,"score_gpt":0.3137458442257338,"score_spread":0.2511373687987485,"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."}}