Editorial: Biogeochemical dynamics in urban systems: interactions, feedbacks and cumulative effects
Bibliographic record
Abstract
Biogeochemical dynamics in urban systems: interactions, feedbacks and cumulative effectsMore than half of the world's population lives in urban areas and the proportion of urban inhabitants continues to increase in most countries (United Nations, 2019).Biogeochemical dynamics in urban systems are unique because of major alterations to hydrological dynamics and surface cover, as well as proximity to anthropogenic emissions of elements, various contaminants, greenhouse gases, and nutrients (Kaye et al., 2006).As urban areas evolve, engineered and/or nature-based solutions such as low-impact development features are also increasingly used to mitigate various impacts of urban development, but likely not yet with fully understood biogeochemical and hydrological implications (Delesantro et al., 2022;Hopkins et al., 2022;Zhang et al., 2023).Understanding the unique biogeochemical cycling dynamics in urban systems remains a major challenge to sustainable urban life and mitigation of downstream impacts.The goal of this Research Topic was to bring diverse scientific and interdisciplinary studies, specific to biogeochemical dynamics in cities, together to advance urban biogeochemical science.Hopefully, these works can collectively help municipal decisionmaking that aims to improve the lives of people and organisms in cities. Biogeochemical dynamics in urban systems are largely, but not entirely, distinct from those in rural or natural landscapes.The cycling of carbon, nitrogen, phosphorus, sulfur, contaminants, and other matter in urban landscapes, water bodies, atmospheres, and green infrastructure such as green roofs continue to be re-thought, particularly in relation to demography, crumbling or renewed infrastructure, global climate change, and interactions among major environmental cycles.As the world continues to urbanize, it is increasingly clear that improving our understanding of biogeochemical dynamics in diverse urban systems at different scales is critical.This Research Topic includes eight original research papers encompassing urban biogeochemical research across the United States, Europe, and Asia.These works have made advances in our understanding of urban salinization and solute mobility (including complex mixtures termed "chemical cocktails"), trace organic compound transformations,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.040 | 0.026 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".