Designing Biodiverse Cities for Mental Health and Wellbeing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Following the Brundtland Report in the early 1990s, the relationship between biodiversity and human wellbeing \nbecame a topic of public debate and scientific research [1]. Nowadays, biodiverse cities can provide ecosystem \nservices as well as mental health and wellbeing. Biodiverse cities have a critical role in delivering services and \ninfrastructure, addressing inequity, and regulating environments that influence human health [2]. Several urban \nhealth issues may be handled with adequate planning and resources, resulting in mutual advantages for human \nand environmental health [2]. However, the health effects of biodiversity loss are becoming more well recognised. \nEcosystem functioning is affected by biodiversity changes, and substantial ecosystem disturbances can result in \nlife-sustaining ecosystem goods and services [3]. As a result, initiatives for increasing and conserving biodiversity \nin cities are required. This research examines case studies of urban green infrastructure, best practices, and policies \nin the United Kingdom and the United States that enhance human health, well-being, and biodiversity conservation. \n1) Naeem, S.; Chazdon, R.; Duffy, J.E.; Prager, C.; Worm, B. Biodiversity and human well-being: an essential link for sustainable development. \nProc. R. Soc. B Biol. Sci. 2016, 283, 20162091. \n2) Secretariat of the Convention on Biological Diversity Cities and Biodiversity Outlook—Executive Summary; Montreal, 2012; ISBN \n9292254375. \n3) WHO Biodiversity and Health Available online: https://www.who.int/news-room/fact-sheets/detail/biodiversity-and-health (accessed \non Aug 5, 2021).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it