{"id":"W2757194187","doi":"10.1007/s11273-017-9576-5","title":"Arrowhead (Sagittaria cuneata) as a bioindicator of nitrogen and phosphorus for prairie streams and wetlands","year":2017,"lang":"en","type":"article","venue":"Wetlands Ecology and Management","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of New Brunswick","funders":"Canadian Water Network; University of Alberta","keywords":"Nutrient; Biology; Bioindicator; Biomass (ecology); Wetland; Aquatic plant; Agronomy; Phosphorus; Population; Botany; Macrophyte; Environmental science; Ecology; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005048239,0.0003023631,0.0003627769,0.0007890783,0.000823439,0.0005394624,0.0004698721,0.0002230373,0.0008910954],"category_scores_gemma":[0.0007638853,0.0001236561,0.0001444962,0.0004479779,0.0003099641,0.0003841071,0.0006531566,0.0002419928,0.00006473847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007779655,"about_ca_system_score_gemma":0.0005999486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03148852,"about_ca_topic_score_gemma":0.1360328,"domain_scores_codex":[0.9996771,0.00008788159,0.000022321,0.0001219796,0.00005376122,0.00003704266],"domain_scores_gemma":[0.9993985,0.000132316,0.0001685386,0.00003038612,0.0001026134,0.0001677058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008904843,0.00048793,0.685334,0.0002220274,0.0001594469,0.0005929506,0.0009228645,0.0007639453,0.2593736,0.0001639071,0.0004011263,0.05068769],"study_design_scores_gemma":[0.00001371708,0.0005040927,0.9926383,0.000009666785,0.00003995834,0.00009719953,0.0006523214,0.001945541,0.00347528,0.00005121553,0.0005616968,0.00001081746],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996641,0.00003150361,0.00007822662,0.00001834287,0.000001335675,0.000005820961,0.0000287744,0.000008096586,0.000163891],"genre_scores_gemma":[0.9990024,0.00003107716,0.0006457484,0.00002783887,0.000001301041,0.000008721803,0.00007654723,0.00000178355,0.0002046563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03148852,"threshold_uncertainty_score":0.06261051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409031466348616,"score_gpt":0.2370939765227483,"score_spread":0.2230036618592622,"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."}}