{"id":"W2318967604","doi":"10.1061/41036(342)375","title":"A Monitoring and Assessment Framework to Evaluate Stream Restoration Needs in Urbanizing Watersheds","year":2009,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2009","topic":"Urban Stormwater Management Solutions","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada); University of Waterloo","funders":"","keywords":"Urban stream; Stream restoration; Watershed; Environmental science; Siltation; Stormwater; Water resource management; Watershed management; Hydrology (agriculture); Environmental resource management; Water quality; Urbanization; STREAMS; Restoration ecology; Detention basin; Environmental planning; Sediment; Surface runoff; Computer science; Ecology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002885131,0.0002824214,0.0002178713,0.0002557843,0.000272331,0.0001529972,0.0001831685,0.00006534199,0.0003572939],"category_scores_gemma":[0.000003042837,0.000227827,0.00003115044,0.0001940189,0.0001557622,0.0004036595,0.0003743778,0.0002418384,0.000143732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003144392,"about_ca_system_score_gemma":0.000001028107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001592402,"about_ca_topic_score_gemma":0.00005498299,"domain_scores_codex":[0.9981913,0.00009152938,0.0003130592,0.0004832737,0.000395598,0.0005252491],"domain_scores_gemma":[0.9994402,0.00002079897,0.00004856559,0.0002742782,0.000001284329,0.0002148801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005728074,0.0001602948,0.9380715,0.000007655298,0.00001721507,0.00003030911,0.006291453,0.00142772,0.02716454,0.00005243187,0.0003425469,0.02637707],"study_design_scores_gemma":[0.0005447985,0.0002038908,0.9590716,0.00009385935,0.00003508849,0.000006046411,0.0005146859,0.0004873728,0.003883608,0.001245117,0.03348447,0.0004294196],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946072,0.0001975728,0.00008006269,0.001471889,0.0001190578,0.000418094,0.000005073548,0.00004906869,0.003052041],"genre_scores_gemma":[0.9926932,0.00007246688,0.002085779,0.0003025628,0.0000667797,0.00003657859,0.000009815936,0.00001978581,0.004712991],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03314193,"threshold_uncertainty_score":0.9290516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01357227351677753,"score_gpt":0.2409540966045502,"score_spread":0.2273818230877727,"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."}}