{"id":"W4298110301","doi":"10.3390/su141912423","title":"Development of an Urban Turfgrass and Tree Carbon Calculator for Northern Temperate Climates","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Turfgrass Adaptation and Management","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Landscape Alberta Nursery Trades Association; University of Guelph","funders":"Texas Tech University","keywords":"Carbon sequestration; Calculator; Carbon fibers; Temperate climate; Environmental science; Urban ecosystem; Carbon flux; Agroforestry; Ecosystem; Natural resource economics; Ecology; Urban planning; Computer science; Carbon dioxide; Biology; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002429743,0.0005200724,0.0004268068,0.002222886,0.0004907703,0.0008495451,0.0009653622,0.0003554173,0.003624242],"category_scores_gemma":[0.004983459,0.0003063538,0.0004415534,0.002361245,0.0002317187,0.0008965501,0.0005692616,0.000315237,0.0006829216],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007870346,"about_ca_system_score_gemma":0.001335901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008078352,"about_ca_topic_score_gemma":0.01510921,"domain_scores_codex":[0.9993687,0.0002109868,0.00006045473,0.0001298915,0.0001953402,0.00003468641],"domain_scores_gemma":[0.9964762,0.001402106,0.0004814815,0.0003843003,0.001085193,0.0001707095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001849785,0.001551156,0.3611626,0.0008395265,0.0002401023,0.0004717145,0.00171589,0.1028571,0.02829376,0.003861345,0.006024481,0.4911326],"study_design_scores_gemma":[0.0002939074,0.001798575,0.4257501,0.0002357278,0.0002958734,0.0005140413,0.001735219,0.4846997,0.04615623,0.003136649,0.0350703,0.0003137912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8403453,0.0001641243,0.1363274,0.0001009028,0.000035688,0.001300153,0.004644754,0.006265113,0.01081661],"genre_scores_gemma":[0.7259994,0.0001318155,0.2666733,0.00002481804,0.000009405719,0.0009417115,0.003337331,0.0005059548,0.002376265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008078352,"threshold_uncertainty_score":0.01606262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007536890236395406,"score_gpt":0.234047704674527,"score_spread":0.2265108144381316,"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."}}